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The document discusses using an ADSP processor to generate 3D images. It describes how the generated image can be rotated in three axes using the processor's assembly instruction set flexibility. X, Y coordinates of the image are input and used to generate deflection signals that control DACs and produce the image on a CRT. The system loads a program from boot memory on reset to execute the image generation program.
Dsp application on mobile communicationKeval Patel
DSP applications on mobile devices include reducing bandwidth for voice communications, implementing low power DSP, and enabling real-time multimedia. Voice communication bandwidth is reduced through speech compression down to 2,400 b/s using spectral analysis of speech segments. Low power DSP is achieved through devices like CADRE that minimize energy usage by reducing supply voltage, switched capacitance, and switching activity. Real-time multimedia requires synchronizing audio and video while accommodating high bandwidth video signals within network constraints through video signal compression.
This document discusses different types of digital signal processors (DSPs). It describes general purpose DSPs that have optimized architectures and instruction sets for digital signal processing operations. It also describes special purpose DSPs that are designed for specific algorithms or applications. Several examples of DSP chips are provided, including the TMS320C3x, TMS320C4x, TMS320C5x, TMS320C55x, and TMS320C62xx. The document also provides an overview of different processor architectures used in DSPs, such as the von Neumann, Harvard, and very long instruction word architectures.
Digital signal processing involves representing and processing signals in the form of discrete numeric values. It has various applications including radar, biomedical monitoring, speech recognition, communications, image processing, and multimedia. Key aspects of digital signal processing implementation are analog to digital conversion, digital processing, and digital to analog conversion. Limitations include information loss due to sampling, aliasing effects, limited frequency resolution, and quantization error. However, digital signal processing provides advantages such as reprogrammability, accuracy control, easy storage and transport of signals, and ability to implement sophisticated algorithms.
Digital: Operating by the use of discrete signals to represent data in the form of numbers.
Signal: A parameter (Electrical quantity or effect) that can be varied in such a way as to convey information.
Processing: A series operations performed according to programmed instructions.
Digital signal processing (DSP) algorithms rely on performing sums of products, which is more efficiently implemented in dedicated DSP processors compared to general purpose processors. DSP processors consume less power and cost less than general purpose processors like Pentium for implementing algorithms involving convolution, filtering, Fourier transforms, and other operations commonly used in DSP. Q-notation specifies the fractional bit representation for fixed-point numbers used in many DSP implementations.
The document discusses using an ADSP processor to generate 3D images. It describes how the generated image can be rotated in three axes using the processor's assembly instruction set flexibility. X, Y coordinates of the image are input and used to generate deflection signals that control DACs and produce the image on a CRT. The system loads a program from boot memory on reset to execute the image generation program.
Dsp application on mobile communicationKeval Patel
DSP applications on mobile devices include reducing bandwidth for voice communications, implementing low power DSP, and enabling real-time multimedia. Voice communication bandwidth is reduced through speech compression down to 2,400 b/s using spectral analysis of speech segments. Low power DSP is achieved through devices like CADRE that minimize energy usage by reducing supply voltage, switched capacitance, and switching activity. Real-time multimedia requires synchronizing audio and video while accommodating high bandwidth video signals within network constraints through video signal compression.
This document discusses different types of digital signal processors (DSPs). It describes general purpose DSPs that have optimized architectures and instruction sets for digital signal processing operations. It also describes special purpose DSPs that are designed for specific algorithms or applications. Several examples of DSP chips are provided, including the TMS320C3x, TMS320C4x, TMS320C5x, TMS320C55x, and TMS320C62xx. The document also provides an overview of different processor architectures used in DSPs, such as the von Neumann, Harvard, and very long instruction word architectures.
Digital signal processing involves representing and processing signals in the form of discrete numeric values. It has various applications including radar, biomedical monitoring, speech recognition, communications, image processing, and multimedia. Key aspects of digital signal processing implementation are analog to digital conversion, digital processing, and digital to analog conversion. Limitations include information loss due to sampling, aliasing effects, limited frequency resolution, and quantization error. However, digital signal processing provides advantages such as reprogrammability, accuracy control, easy storage and transport of signals, and ability to implement sophisticated algorithms.
Digital: Operating by the use of discrete signals to represent data in the form of numbers.
Signal: A parameter (Electrical quantity or effect) that can be varied in such a way as to convey information.
Processing: A series operations performed according to programmed instructions.
Digital signal processing (DSP) algorithms rely on performing sums of products, which is more efficiently implemented in dedicated DSP processors compared to general purpose processors. DSP processors consume less power and cost less than general purpose processors like Pentium for implementing algorithms involving convolution, filtering, Fourier transforms, and other operations commonly used in DSP. Q-notation specifies the fractional bit representation for fixed-point numbers used in many DSP implementations.
This document provides an overview of digital signal processing (DSP). It begins by defining an analog signal and a digital signal. It then describes the basic components of a DSP system, which includes an analog-to-digital converter (ADC) to convert the analog input signal to digital, a digital signal processor to process the digital signal, and a digital-to-analog converter (DAC) to reconstruct the analog output signal. Finally, it discusses some advantages and limitations of DSP systems compared to analog systems and provides examples of DSP applications.
Mp3 player working by digital signal processingDipanjon Halder
MP3 uses lossy data compression to reduce the size of digital audio files. It works by analyzing sound within short windows in both the time and frequency domains. It exploits the principles of simultaneous and temporal masking, where certain sounds can mask others that are softer. This allows it to reduce the precision of inaudible audio components. By doing so, MP3 is able to significantly reduce the data rate needed for audio files while still maintaining near-CD quality. For example, a typical 5-minute song compressed to MP3 at 128kbps would be only 4.8MB in size, allowing over 3,000 songs to fit on a 16GB MP3 player.
The document provides information about the Waves L2 audio processor software. The L2 combines advanced peak limiting, level maximization, and Increased Digital Resolution (IDR) processing. IDR uses dithering and noise shaping to maximize digital resolution when reducing bit depth. The L2 allows processing at 48-bit precision and outputting at 24-bit for archiving. It includes Auto Release Control and offers various dither types, noise shaping curves, and output bit depths for different applications.
Application of digital_signal_processing_in_audio_processing[1]Sveris COE Pandharpur
This document discusses digital signal processing applications in audio processing. It covers topics like digital audio mixing, speech synthesis and recognition, and the compact disk digital audio system. Audio signals can be represented digitally or analog, and processing can occur in either domain by altering the signals mathematically or electrically. Applications of audio processing are necessary for broadcasting, as it addresses problems transmitting audio from the studio to transmitter. The compact disk digital audio system section focuses on CD and digital audio tape technology for music recording and playback.
Digital Audio Tape (DAT) is a recording and playback medium developed by Sony in the 1980s that uses magnetic tape similar to audio cassettes. DAT supports lossless data compression and allows sampling at various rates up to 48 kHz and 16 bits. DAT tapes range in length from 15 to 180 minutes depending on the amount of data stored. DAT was used professionally for master recordings and in the computer industry for data backups but was never widely adopted for home use.
Audio compression reduces the size of audio files through lossy or lossless techniques. Lossy compression uses psychoacoustic algorithms to filter out sounds imperceptible to humans, reducing file size but introducing data loss. Lossless compression compresses files without any loss, allowing perfect restoration. Common lossy codecs include MP3, while lossless options are FLAC, ALAC, and WMA Lossless. International standards bodies like MPEG and ITU-T develop and standardize audio compression formats.
In this presentation, production of digital audio is discussed. Also brief introduction about digital audio broadcast, recording techniques and stereo phony is given.
This document discusses digital signal processing (DSP). It begins with an introduction to DSP and defines different types of signals like analog, discrete, causal and random signals. It then explains the basic concepts of DSP systems including filters. The document discusses analog and digital filters in detail. It describes the two main types of digital filters - FIR and IIR filters. Finally, it provides examples of using DSP techniques for applications like audio effects generation and image processing.
This document summarizes the various equipment found at a radio station, including equipment in the studio, rack room, and transmitter site. In the studio, key equipment includes the audio console, microphones, playback devices, monitors, and various control panels. The rack room contains networking, audio processing, and automation equipment. The transmitter site houses equipment to transmit the audio signal such as the exciter, amplifier, and antenna array.
Practical Digital Signal Processing for Engineers and TechniciansLiving Online
Describe the fundamentals of Digital Signal Processing (DSP)
Apply DSP technology to improve efficiency
Analyse frequency of signals and the application of this knowledge
Correctly apply design digital filters
Analyse the performance of DSP systems
Identify the key issues in designing a DSP system
Specify features and capabilities of commercial DSP applications
WHO SHOULD ATTEND?
Condition monitoring engineers and technicians
Control system engineers
Communications system engineers
Design engineers
Electrical and electronic engineers
Instrumentation engineers
MORE INFORMATION: http://www.idc-online.com/content/practical-digital-signal-processing-engineers-and-technicians-2
This document provides an overview of a webinar on digital signal processing. It introduces the presenter, Dr. Steve Mackay, and provides instructions for interacting during the webinar. It then gives brief biographical information about Dr. Mackay. The remainder of the document outlines key topics to be covered, including definitions of digital and analog signals, applications of DSP, sampling theory, and analog to digital conversion. Diagrams are provided to illustrate various DSP concepts and systems.
Digital signal processing (DSP) involves analyzing, interpreting, and manipulating signals in a digital representation. DSP became prominent with advances in digital electronics and fast Fourier transform algorithms. Modern DSPs are optimized for multiply-accumulate operations and real-time processing using fixed-point arithmetic. The four biggest DSP manufacturers are Texas Instruments, Freescale, Lucent Technologies, and Analog Devices.
This document provides an overview of several key topics related to analog and digital technologies:
1) It explains the basic concepts of analog and digital signals and technologies, and discusses the importance of frequency spectrum and bandwidth for communication.
2) It gives an overview of digital technologies and how data is digitized for processing and transmission. Key topics covered include digitization of data, audio, images and video.
3) It discusses interfaces between analog and digital technologies, and factors that influence quality retention when data is digitized and transmitted digitally.
Software-defined radio (SDR) uses software for signal processing tasks like modulation and demodulation, replacing analog hardware components in traditional radios. SDR allows radios to be more flexible and reconfigurable through software updates. A typical SDR system uses an analog front-end to convert radio signals to digital and a digital signal processor to perform signal processing through software. SDR provides benefits like more customizable radios, lower development costs, and easier upgrades compared to traditional hardware radios.
The TMS320C4672 is a six-Core DSP from Texas Instrument that can be cascaded into larger system and interface to a FPGA from doing Real-World connectivity.
This presentation provide some Application example for MultiCore DSP solutions
This document provides an overview of audio compression technologies. It discusses what audio is, why compression is needed, and the main types of audio compression: lossy and lossless. It describes some standard codecs for each type including MP3, AAC, FLAC. It explains the MPEG audio encoding and decoding process, and notes that AAC is the successor to MP3. In summary, the document covers audio fundamentals and provides details on common audio compression standards and techniques.
Partitioning Data Acquisition Systems (Design Conference 2013)Analog Devices, Inc.
Acquired analog signals can be manipulated and processed by either the analog or digital portions of a system, for example, through filtering, multiplexing, and gain control. The analog portions of a system can typically provide reasonably simple processing at fairly low cost, power, and overhead. Digital processing can provide far greater analysis power and can alter the nature of the analysis without changing hardware. Sampling theory, however, must be taken into account. This session covers the signal chain basics from signal to sensor to amplifier to converter to digital processor and back out again.
This presentation provides an overview of digital signal processing (DSP). It defines key terms like signal and signal processing and explains the basic principles and components of DSP systems. The presentation notes that DSP has advantages over analog processing like accuracy, flexibility, and ease of operation. It provides examples of DSP applications in areas like audio, communications, biomedicine, and more. In conclusion, the presentation emphasizes that DSP involves manipulating digital numbers using programmed instructions and is widely used in modern applications.
Advanced Topics In Digital Signal ProcessingJim Jenkins
This four-day course from Applied Technology Institute examines advanced digital signal processing techniques used in modern fourth generation modems. The course will cover topics such as digital filters, channelizers, filter design techniques, digital baseband transmission, signal conditioning, sigma-delta converters, carrier centered modulation and demodulation, synchronization, and adaptive filters. Students will learn how to size and design efficient digital filters, understand multirate signal processing, and limitations of DSP-based solutions. The instructor, Dr. Fred Harris, is an expert in DSP and its applications in communication systems.
Ieee 2009 J2 Ee Projects, Ieee 2009 J2 Me Projectsncct
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This document provides an overview of digital signal processing (DSP). It begins by defining an analog signal and a digital signal. It then describes the basic components of a DSP system, which includes an analog-to-digital converter (ADC) to convert the analog input signal to digital, a digital signal processor to process the digital signal, and a digital-to-analog converter (DAC) to reconstruct the analog output signal. Finally, it discusses some advantages and limitations of DSP systems compared to analog systems and provides examples of DSP applications.
Mp3 player working by digital signal processingDipanjon Halder
MP3 uses lossy data compression to reduce the size of digital audio files. It works by analyzing sound within short windows in both the time and frequency domains. It exploits the principles of simultaneous and temporal masking, where certain sounds can mask others that are softer. This allows it to reduce the precision of inaudible audio components. By doing so, MP3 is able to significantly reduce the data rate needed for audio files while still maintaining near-CD quality. For example, a typical 5-minute song compressed to MP3 at 128kbps would be only 4.8MB in size, allowing over 3,000 songs to fit on a 16GB MP3 player.
The document provides information about the Waves L2 audio processor software. The L2 combines advanced peak limiting, level maximization, and Increased Digital Resolution (IDR) processing. IDR uses dithering and noise shaping to maximize digital resolution when reducing bit depth. The L2 allows processing at 48-bit precision and outputting at 24-bit for archiving. It includes Auto Release Control and offers various dither types, noise shaping curves, and output bit depths for different applications.
Application of digital_signal_processing_in_audio_processing[1]Sveris COE Pandharpur
This document discusses digital signal processing applications in audio processing. It covers topics like digital audio mixing, speech synthesis and recognition, and the compact disk digital audio system. Audio signals can be represented digitally or analog, and processing can occur in either domain by altering the signals mathematically or electrically. Applications of audio processing are necessary for broadcasting, as it addresses problems transmitting audio from the studio to transmitter. The compact disk digital audio system section focuses on CD and digital audio tape technology for music recording and playback.
Digital Audio Tape (DAT) is a recording and playback medium developed by Sony in the 1980s that uses magnetic tape similar to audio cassettes. DAT supports lossless data compression and allows sampling at various rates up to 48 kHz and 16 bits. DAT tapes range in length from 15 to 180 minutes depending on the amount of data stored. DAT was used professionally for master recordings and in the computer industry for data backups but was never widely adopted for home use.
Audio compression reduces the size of audio files through lossy or lossless techniques. Lossy compression uses psychoacoustic algorithms to filter out sounds imperceptible to humans, reducing file size but introducing data loss. Lossless compression compresses files without any loss, allowing perfect restoration. Common lossy codecs include MP3, while lossless options are FLAC, ALAC, and WMA Lossless. International standards bodies like MPEG and ITU-T develop and standardize audio compression formats.
In this presentation, production of digital audio is discussed. Also brief introduction about digital audio broadcast, recording techniques and stereo phony is given.
This document discusses digital signal processing (DSP). It begins with an introduction to DSP and defines different types of signals like analog, discrete, causal and random signals. It then explains the basic concepts of DSP systems including filters. The document discusses analog and digital filters in detail. It describes the two main types of digital filters - FIR and IIR filters. Finally, it provides examples of using DSP techniques for applications like audio effects generation and image processing.
This document summarizes the various equipment found at a radio station, including equipment in the studio, rack room, and transmitter site. In the studio, key equipment includes the audio console, microphones, playback devices, monitors, and various control panels. The rack room contains networking, audio processing, and automation equipment. The transmitter site houses equipment to transmit the audio signal such as the exciter, amplifier, and antenna array.
Practical Digital Signal Processing for Engineers and TechniciansLiving Online
Describe the fundamentals of Digital Signal Processing (DSP)
Apply DSP technology to improve efficiency
Analyse frequency of signals and the application of this knowledge
Correctly apply design digital filters
Analyse the performance of DSP systems
Identify the key issues in designing a DSP system
Specify features and capabilities of commercial DSP applications
WHO SHOULD ATTEND?
Condition monitoring engineers and technicians
Control system engineers
Communications system engineers
Design engineers
Electrical and electronic engineers
Instrumentation engineers
MORE INFORMATION: http://www.idc-online.com/content/practical-digital-signal-processing-engineers-and-technicians-2
This document provides an overview of a webinar on digital signal processing. It introduces the presenter, Dr. Steve Mackay, and provides instructions for interacting during the webinar. It then gives brief biographical information about Dr. Mackay. The remainder of the document outlines key topics to be covered, including definitions of digital and analog signals, applications of DSP, sampling theory, and analog to digital conversion. Diagrams are provided to illustrate various DSP concepts and systems.
Digital signal processing (DSP) involves analyzing, interpreting, and manipulating signals in a digital representation. DSP became prominent with advances in digital electronics and fast Fourier transform algorithms. Modern DSPs are optimized for multiply-accumulate operations and real-time processing using fixed-point arithmetic. The four biggest DSP manufacturers are Texas Instruments, Freescale, Lucent Technologies, and Analog Devices.
This document provides an overview of several key topics related to analog and digital technologies:
1) It explains the basic concepts of analog and digital signals and technologies, and discusses the importance of frequency spectrum and bandwidth for communication.
2) It gives an overview of digital technologies and how data is digitized for processing and transmission. Key topics covered include digitization of data, audio, images and video.
3) It discusses interfaces between analog and digital technologies, and factors that influence quality retention when data is digitized and transmitted digitally.
Software-defined radio (SDR) uses software for signal processing tasks like modulation and demodulation, replacing analog hardware components in traditional radios. SDR allows radios to be more flexible and reconfigurable through software updates. A typical SDR system uses an analog front-end to convert radio signals to digital and a digital signal processor to perform signal processing through software. SDR provides benefits like more customizable radios, lower development costs, and easier upgrades compared to traditional hardware radios.
The TMS320C4672 is a six-Core DSP from Texas Instrument that can be cascaded into larger system and interface to a FPGA from doing Real-World connectivity.
This presentation provide some Application example for MultiCore DSP solutions
This document provides an overview of audio compression technologies. It discusses what audio is, why compression is needed, and the main types of audio compression: lossy and lossless. It describes some standard codecs for each type including MP3, AAC, FLAC. It explains the MPEG audio encoding and decoding process, and notes that AAC is the successor to MP3. In summary, the document covers audio fundamentals and provides details on common audio compression standards and techniques.
Partitioning Data Acquisition Systems (Design Conference 2013)Analog Devices, Inc.
Acquired analog signals can be manipulated and processed by either the analog or digital portions of a system, for example, through filtering, multiplexing, and gain control. The analog portions of a system can typically provide reasonably simple processing at fairly low cost, power, and overhead. Digital processing can provide far greater analysis power and can alter the nature of the analysis without changing hardware. Sampling theory, however, must be taken into account. This session covers the signal chain basics from signal to sensor to amplifier to converter to digital processor and back out again.
This presentation provides an overview of digital signal processing (DSP). It defines key terms like signal and signal processing and explains the basic principles and components of DSP systems. The presentation notes that DSP has advantages over analog processing like accuracy, flexibility, and ease of operation. It provides examples of DSP applications in areas like audio, communications, biomedicine, and more. In conclusion, the presentation emphasizes that DSP involves manipulating digital numbers using programmed instructions and is widely used in modern applications.
Advanced Topics In Digital Signal ProcessingJim Jenkins
This four-day course from Applied Technology Institute examines advanced digital signal processing techniques used in modern fourth generation modems. The course will cover topics such as digital filters, channelizers, filter design techniques, digital baseband transmission, signal conditioning, sigma-delta converters, carrier centered modulation and demodulation, synchronization, and adaptive filters. Students will learn how to size and design efficient digital filters, understand multirate signal processing, and limitations of DSP-based solutions. The instructor, Dr. Fred Harris, is an expert in DSP and its applications in communication systems.
Ieee 2009 J2 Ee Projects, Ieee 2009 J2 Me Projectsncct
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
Domain Wise Project Titles, 2009 2010 Ncct Final Year Projectsncct
The document provides information about NCCT, an organization that offers final year engineering projects. It lists over 75 potential project domains including embedded systems, robotics, biomedical, communication, automation and more. It also lists examples of specific project ideas in areas like robotics, intelligent transportation systems, and biomedical. The document promotes NCCT by highlighting qualities like quality training, excellent support, and guidance provided for project completion.
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O N L I N E V E H I C L E R E N T A L S Y S T E M V R Sncct
This document describes a project to develop an online vehicle rental system (VRS) to automate the manual and time-consuming vehicle rental reservation process. The goals are to reduce customer losses to competitors, save costs, and improve customer satisfaction. The VRS will manage a database of vehicle inventory and reservations. It will generate bi-weekly reports on vehicle costs, maintenance needs, and rental revenue. The system may later be upgraded to support business-to-business functions and enterprise-wide vehicle rental across multiple companies.
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
Digital Signal Processing (DSP) converts analog signals into digital data that can be analyzed more easily in digital form. Scientech Technologies' DSP Lab 2.0 is an integrated solution for establishing a DSP-based embedded systems lab using a TI 6000 platform to learn digital signal processing and real-time DSP applications. The lab includes hardware, software, and experiments to perform tasks like sampling, filtering, modulation, and audio signal processing.
REAL TIME SPECIAL EFFECTS GENERATION AND NOISE FILTRATION OF AUDIO SIGNAL USI...ijcsa
Digital signal processing is being increasingly used for audio processing applications. Digital audio effects
refer to all those algorithms that are used for enhancing sound in any of the steps of a processing chain of
music production. Real time audio effects generation is a highly challenging task in the field of signal
processing. Now a day, almost every high end multimedia audio device does digital signal processing in
one form or another. For years musicians have used different techniques to give their music a unique
sound. Earlier, these techniques were implemented after a lot of work and experimentation. However, now
with the emergence of digital signal processing this task is simplified to a great extent. In this article, the
generations of special effects like echo, flanging, reverberation, stereo, karaoke, noise filtering etc are
successfully implemented using MATLAB and an attractive GUI has been designed for the same.
The document describes three types of embedded systems: small scale, medium scale, and sophisticated. Small scale systems use a single microcontroller with little hardware/software complexity. Medium scale systems can use multiple microcontrollers or DSPs with more complex hardware/software. Sophisticated systems have significant hardware/software complexity and may require specialized processors. The document also discusses different types of processors used in embedded systems like microprocessors, microcontrollers, DSPs, and application-specific processors.
The document discusses using FPGAs for medical imaging applications like CT scanners. It describes how FPGAs can be used to distribute data to and from DSPs, act as a coprocessor to a DSP, or replace DSPs altogether by using soft CPU and parallel processing structures. An FPGA coprocessing solution leverages existing DSP software while using the FPGA to accelerate processing-intensive code. FPGAs offer benefits over DSPs like higher clock rates, more instructions per cycle, and more flexible I/O. They are increasingly important for medical imaging due to their ability to handle high performance processing needs.
This document discusses digital signal processors and customizable processors. It begins by describing digital signal processors, noting they are used for digital signal processing tasks like filtering, estimation, and data manipulation in real time. It then discusses customizable processors and the benefits of customization, as well as using microprocessor cores in system-on-chip designs. The rest of the document provides details on digital signal processing, including digital to analog conversion, applications of DSP like finite impulse response filtering using general purpose and digital signal processors, and features of the TMS32010 digital signal processor.
The document describes an MP3 player project using an Atmega microcontroller. The MP3 player stores audio files in MP3 format on an SD card and allows users to select songs using a keypad. It includes an Atmega 162 microcontroller to control an LCD display and keypad, as well as a DSP processor to convert MP3 files to clear audio in real time. The document discusses the components used, including the microcontroller, LCD, DSP processor, and USBASP programmer. It provides details on how these components interface and are programmed to build a functioning MP3 player.
The document provides an overview of audio recording systems and processes. It discusses the importance of understanding computer hardware components like the CPU, motherboard, RAM, and sound card for digital audio work. It describes the digital recording process which involves filtering, sampling, analog-to-digital conversion, and data coding/correction. The reproduction process reverses these steps. Hard disk recording systems offer advantages like handling long samples, random access editing, and non-destructive editing.
Speech Recognition Systems(SRS) have been implemented by various processors including the digital signal processors(DSPs) and field programmable gate arrays(FPGAs) and their performance has been reported in literature. The fundamental purpose of speech is communication, i.e., the transmission of messages.In the case of speech, the fundamental analog form of the message is an acoustic waveform, which we call the speech signal. Speech signals can be converted to an electrical waveform by a microphone, further manipulated by both analog and digital signal processing, and then converted back to acoustic form by a loudspeaker, a telephone handset or headphone, as desired.The recognition of speech requires feature extraction and classification. The systems that use speech as input require a microcontroller to carry out the desired actions. In this paper, Cypress Programmable System on Chip (PSoC) has been studied and used for implementation of SRS. From all the available PSoCs, PSoC5 containing ARM Cortex-M3 as its CPU is used. The noise signals are firstly nullified from the speech signals using LogMMSE filtering. These signals are then sent to the PSoC5 wherein the speech is recognized and desired actions are performed.
Speech Recognition Systems(SRS) have been implemented by various processors including the digital signal processors(DSPs) and field programmable gate arrays(FPGAs) and their performance has been reported in literature. The fundamental purpose of speech is communication, i.e., the transmission of messages.In the case of speech, the fundamental analog form of the message is an acoustic waveform, which we call the speech signal. Speech signals can be converted to an electrical waveform by a microphone, further manipulated by both analog and digital signal processing, and then converted back to acoustic form by a loudspeaker, a telephone handset or headphone, as desired.The recognition of speech requires feature extraction and classification. The systems that use speech as input require a microcontroller to carry out the desired actions. In this paper, Cypress Programmable System on Chip (PSoC) has been studied and used for implementation of SRS. From all the available PSoCs, PSoC5 containing ARM Cortex-M3 as its CPU is used. The noise signals are firstly nullified from the speech signals using LogMMSE filtering. These signals are then sent to the PSoC5 wherein the speech is recognized and desired actions are performed.
AXONIM Devices - expert in design and development of the embedded electronics on RTOS, complex/single board computers, digital signal processing algorithms, electronics processor devices, PCBA, digital circuits, hardware, firmware development, enterprise hardware & software solutions, distributing systems.
Electronic embedded systems development, electronic devices design, algorithms and software are the main areas of activity of the AXONIM.
The development process starts with an assessment of the customer's technical requirements of the project that is done by our expert group, if required they perform research and write technical specification, then project team prepares working project plan.
The immediate development of a technical system - device, embedded electronic system, or electronic module consists of the design of the hardware platform, software development, device body design, further prototyping - manufacturing of prototypes and the subsequent technical support throughout the life cycle of the device.
Our competences include, but are not limited with the following types of engineering tasks: algorithms for digital signal processing (filtering, processing of audio and video streams, encoding / decoding, compression / decompression), data collection systems, electronic optical devices, porting BSP embedded OS (Windows Embedded, Linux, Android, eCos, freeRTOS) and others. The result of our service is a full-featured prototype device and a set of design documentation, which allows to start production of the final product.
Software Design of Digital Receiver using FPGAIRJET Journal
This document describes the design and implementation of a digital receiver using an FPGA. It involves sampling an analog signal from a radar target using an ADC at a high sampling rate. This sampled signal is then sent to a digital down converter (DDC) which performs frequency translation and decimation. The DDC is implemented using IP cores on an FPGA. It translates the sampled signal to a lower frequency and outputs I and Q signals at a lower sampling rate. This provides a digital signal with higher precision and stability for extracting information from radar targets.
1. The document provides definitions for audio and sound design terms, sourced from online references. It includes terms related to sound file formats, limitations of early computer audio hardware, audio recording and sampling techniques, and MIDI instrumentation.
2. Students are tasked with researching definitions for provided terms and citing sources, then describing how the terms relate to their own audio production work.
3. The glossary covers topics from foley artistry and sound libraries to uncompressed audio formats, lossy compression, digital audio tape, and sampling bit-depth and rates.
presentation on digital signal processingsandhya jois
The document discusses digital signal processing (DSP). It defines key terms like digital, signal, and processing. It explains how analog signals are converted to digital form by sampling and quantization. It also describes common digital modulation schemes and compares DSP processors to microprocessors. Finally, it discusses digital filters and their types as well as applications of DSP in areas like audio processing, communications, and imaging.
DIGITAL SIGNAL PROCESWSING AND ITS APPLICATIONLokeshBanarse
Digital signal processing (DSP) involves using digital technology to process analog signals. It converts analog signals into digital data that can be manipulated and analyzed. DSP has applications in areas like audio processing, image processing, radar, and mobile phones. The key components of DSP systems are program memory, data memory, a compute engine, and input/output interfaces. DSP emerged in the 1960s and was initially used for applications like radar, sonar, and space exploration. It later expanded into commercial uses with the growth of personal computers and consumer electronics.
The document describes the design and development of an RDS (Radio Data System) encoder that the author worked on from 2011-2012 at TAKTA Company. Some key points:
- The RDS encoder allows digital information like time, advertising, and text messages to be transmitted alongside FM radio broadcasts.
- The author's role included designing circuits and programming, assembling prototypes, testing, and managing the project.
- Technical specifications of the RDS encoder include supporting all RDS groups and protocols, interfaces for serial, TCP/IP, and I/O, and features for transmitting information like station name, program type, radio text, and traffic messages.
1. Analog-to-digital conversion (ADC) allows computers to interact with analog signals by sampling and quantizing analog signals from devices like CD players.
2. During recording, an ADC converts an analog audio signal into a digital format by repeatedly measuring and assigning a binary number to the signal's amplitude at set intervals defined by the sample rate.
3. During playback, a digital-to-analog converter (DAC) reconverts the digital numbers back into an analog signal by combining the amplitude information from each sample to rebuild the original wave.
This document provides an introduction to digital signal processing (DSP). It defines signal processing and distinguishes between analog signal processing (ASP) and DSP. For DSP, analog signals are first converted to digital using analog-to-digital converters before processing, while for ASP entire processing is done in analog domain. Some key advantages of DSP over ASP include more compact size, accuracy, flexibility, easy storage and modification of digital signals. Additional complexity of analog-to-digital and digital-to-analog conversion is a disadvantage of DSP.
Introduction to digital signal processing 2Hossam Hassan
The document discusses digital signal processing. It begins by listing the objectives, which include explaining how analog signals are converted to digital form through sampling and analog-to-digital conversion. It then covers digital signal processing basics, how analog signals are converted to digital via sampling and ADCs, different types of ADCs, digital signal processors and their applications, and digital-to-analog conversion.
The document discusses a digital signal processing (DSP) and field programmable gate array (FPGA) video starter kit. It includes a DSP FPGA development board, image sensor, and software. The kit is used to design systems for applications like machine vision, surveillance, and automotive driver assistance through image processing on the FPGA.
Biomedical Wearable Device For Remote Monitoring Ofphysiological Signalsncct
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
Digital Water Marking For Video Piracy Detectionncct
The document proposes a digital watermarking system to detect video piracy. Digital watermarks contain copyright information embedded in videos. The proposed system spreads watermarks throughout videos and makes them invisible, preventing easy removal. It embeds owner/distributor details, serial numbers and transaction dates. This allows tracing pirated videos back to their source by extracting the watermark information. The system overcomes issues like visible, concentrated watermarks in existing systems.
Self Repairing Tree Topology Enabling Content Based Routing In Local Area Ne...ncct
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
Botminer Clustering Analysis Of Network Traffic For Protocol And Structure...ncct
This document describes BotMiner, a framework for detecting botnets through analysis of network traffic in a monitored network. BotMiner aims to be protocol- and structure-independent by focusing on the intrinsic communication and activity characteristics of botnets. It clusters similar communication and malicious activity patterns to identify hosts that likely belong to the same botnet. BotMiner monitors traffic for the C-plane (command and control communication) and A-plane (malicious activity). It clusters flows in each plane and performs cross-cluster correlation to detect bots by finding hosts that share patterns in both planes. The goal is to generate low false positives/negatives while requiring reasonable computational resources.
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
This document describes Cryptkit, a Java-based cryptographic system that implements encryption algorithms like TDES, RSA, RABIN, and PC-1 to enhance network security. It uses both symmetric and asymmetric encryption and supports any operating system. The purpose is to provide real-time encryption over networks using robust standard algorithms. Future enhancements may include mobile messaging security and additional multimedia encryption capabilities.
This document contains a list of over 100 project titles and descriptions completed using VB.NET, C#, ASP.NET and databases like SQL Server and Oracle. The projects cover a wide range of domains including network monitoring systems, CRM systems, image processing, ERP implementations and more. The company provides .NET project development and training to students.
This document lists over 50 projects related to Java, J2EE, and J2ME offered by NCCT. The projects cover a wide range of domains and technologies including distributed systems, databases, networking, security, and more. Many of the projects involve implementing IEEE papers. NCCT provides guidance and support to help students complete the projects on time to gain real-world experience with the latest tools and technologies.
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
This document provides summaries of research papers from IEEE transactions from 2007-2009. It includes an index listing years with instructions to use Ctrl+F to search for papers from a specific year. Some example papers summarized include ones on contention-aware performance analysis of mobility-assisted routing, opportunistic scheduling with reliability guarantees in cognitive radio networks, and efficient multi-party digital signature using adaptive secret sharing for low-power devices in wireless networks. The document provides abstracts and keywords for several technical research papers.
Engineering College Projects, M C A Projects, B E Projects, B Tech Pr...ncct
1. NCCT is a company located in Chennai, India that offers IEEE and non-IEEE software projects.
2. They provide projects in various domains including networking, mobile computing, web applications, image processing, and more.
3. NCCT offers project deliverables including a project abstract, IEEE paper, presentation, report, and certification. They also provide supporting materials and documentation.
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I E E E 2009 Java Projects, I E E E 2009 A S Pncct
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final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
Software Projects Java Projects Mobile Computingncct
NCCT is an organization that offers IEEE and non-IEEE projects in various domains including mobile computing, networking, secure computing, and others. It provides project support and deliverables such as project abstracts, reports, presentations, and certification. NCCT is located in Chennai, India and provides contact information including phone numbers, email, and website for students to obtain more details on available projects.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Dsp
1. 3D IMAGE GENERATION USING ADSP
The DSP processors are commonly used to handle the image
data, where the image has to be processed digitally and
accurately, such as the application like scanning systems in Bio-
medial Field.
The processor has powerful instruction sets and most of the
instructions are one cycle execution. So that the result can be
obtained much faster and efficient, which is required for Analog
signal processing.
In this project, we are generating a 3D image using ADSP (DSP)
processor. The generated Image can be rotated in 3-axis (X,Y &
Z) using flexibility of the assembly instruction set of the processor.
Initially we draw the Image in a graph sheet and take X,Y co-
ordinates of the image. This data will be input to our systems
This can be obtained from the sensor used for scanning in Real
time
The Software is developed such that it can take these data and
generates the X & Y deflection signal.
The hardware has a DSP with Boot memory. The developed
firmware will be loaded in EPROM and it will be configured as
Boot memory for DSP.
On reset the Processor loads the data (program) from the Boot
memory to its internal Program memory and starts executing the
Program.
Two DACs (Digital to Analog Converter) are used to control the X
& Y deflection of CRT. So the software controls these two DACs
and generates the Image in CRT.
We can also use a CRO as CRT in X-Y mode. The signal given to
the Channel1 of CRO may deflect the dot X-direction and
Channel2 for Y-direction.
2. ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP
technology which processes the signal to eliminate unwanted
noise and improve incoming signal
DSP
DSP stands for Digital Signal Processor. DSP chips are widely
used in sound cards, fax machines, modems, cellular phones,
high-capacity hard disks and digital TVs
DSP chips are used in sound cards for recording and playback
and speech synthesis. Other audio uses are amplifiers that
simulate concert halls and surround-sound effects for music and
home theater
Digital Signal Processing uses mathmatics to operate on a digital
signal (such as a digital audio stream) to generate some type of
altered output. DSP is used heavily in software and hardware
effects processing.
DSP chips are found on an increasing number of sound cards to
provide extra audio processing power and help relieve the
computers CPU of this type of work, much like a 3D graphics
accelerator would for rendering 3D graphics
3. 3D IMAGE GENERATION USING ADSP
BLOCK DIAGRAM
BOOT
MEMORY
ADSP
PROCESSOR
DAC 1
8Bit
DAC 2
8Bit
TO CRO
CH1
TO CRO
CH2
DATA
MEMORY
4. ADAPTIVE FILTER IMPLEMENTATION
ADAPTIVE FILTER IMPLEMENTATION
ADAPTIVE FILTER IMPLEMENTATION
ADAPTIVE FILTER IMPLEMENTATION
The aim of the project is to develop a digital system to perform adaptive
filtering of analog signals.
Adaptive filters are used to accomplish a variety of applications,
including
1. Echo cancellation in Voice or Data signals.
2. Noise cancellation in Speech, Audio and Biomedical signal
processing.
3. Channel equalizations in Data communication to minimize the effect
of intersymbol interference
BASICS OF ADAPTIVE DIGITAL FILTERS
Adaptive filter can be implemented from the FIR filters. Normally, in FIR
filters, the filter coefficients are constant. But in the adaptive FIR filters,
the filter coefficients are adjusted to minimize the errors.
Thus when we employ adaptive filter for echo cancellation, the FIR filter
coefficients are adjusted in every cycle to remove the echo from the
input. Adaptive filters can be implemented using the least Mean-square
(LMS) algorithm.
HARDWARE
The block diagram of ADSP system used for adaptive filtering is shown
in Fig.1. The system consists of ADSP as CPU, CODEC, EPROM,
RAM, Amplifier circuits, MIC and speaker. The CODEC has been used
for analog input and output.
The CODEC has been interfaced to ADSP through its serial port. The
optional hardware includes PC interfacing circuit consisting of serial
Input port and RS 232 level converter. The additional serial Input port
have been developed using buffer.
FUNCTIONING
The analog input signal from MIC are amplified and fed to CODEC. The
CODEC converts the analog signal into digital data and transfer the
data to DSP microprocessor.
The processor adds echo to the input and it will output the signal with
echo to the speaker.
5. The signal with echo can be stored in memory and then adaptive filter
can be introduced so as to remove the echo from the input signal.
After introducing the adaptive filter, we can hear that the echo is slowly
removed.
The adaptive filter coefficients are also output to CODEC which
converts the digital filter coefficients to analog and they can be viewed
on the CRO.
APPLICATIONS OF ADAPTIVE FILTER
Digital Audio
Digital Graphical Equalizer
Noise removal
High Speed Modems
Noise removal in ECG signals
ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP
technology which processes the signal to eliminate unwanted noise
and improve incoming signal
DSP
DSP stands for Digital Signal Processor. DSP chips are widely used in
sound cards, fax machines, modems, cellular phones, high-capacity
hard disks and digital TVs
DSP chips are used in sound cards for recording and playback and
speech synthesis. Other audio uses are amplifiers that simulate
concert halls and surround-sound effects for music and home theater
Digital Signal Processing uses mathmatics to operate on a digital
signal (such as a digital audio stream) to generate some type of
altered output. DSP is used heavily in software and hardware effects
processing.
DSP chips are found on an increasing number of sound cards to
provide extra audio processing power and help relieve the computers
CPU of this type of work, much like a 3D graphics accelerator would
for rendering 3D graphics
6. PC
RS 232c
LEVEL
CONVER
TER
SY
STEMBU
S
B
U
FFE
R DA
C CRO
Optional
H
ardware
AMP
SERIALINPUT
PORT
Power Amp
Pre Amp
Speaker
Mike
CODEC AD
SP
-2105
EPROM RAM
Fig
1.
Block
diagram
of
ADSP
-2105
system
used
for
adaptive
filtering
7. DTMF GENERATION AND
DETECTION
The aim of the project is to develop a digital system for generation and
detection of DTMF tones. The DTMF (Dual Tone Multifrequency) are used
in Modern push button telephones.
The push button telephones are replacing the conventional dial-pulse
signaling in telephone networks worldwide.
PRINCIPLE
The DTMF tones are sinusoid signals of standard frequencies defined by
CCITT (Consultative Committee for International Telephones and
Telegraphy).
In push-button telephones, for each digit, two tones are assigned. One
tone is chosen out of 4 Row tones and the other is chosen out of 4 column
tones.
By this combination, 16 different DTMF digits can be formed as
shown in figure below.
The DTMF tones can be easily generated or detected using DSP
microprocessor based system.
DTMF tones can be generated using function generation programs and
DTMF tones can be detected by performing FFT analysis of the signals.
8. The FFT of a signal will give the frequency components of the signal and
from the knowledge of frequency component, the DTMF digit can be
identified.
HARDWARE
BLOCK DIAGRAM OF ADSP
DTMF GENERATION AND DETECTION
The system consists of ADSP-2105 as CPU, CODEC, EPROM, RAM,
Amplifier circuits, MIC and speaker. The CODEC has been used for
analog input and output, the CODEC has been interfaced to ADSP-2105
through its serial port.
The optional hardware includes PC interfacing circuit consisting of serial
Input port and RS 232 level converter. The additional serial Input port
have been developed using buffer.
FUNCTIONING
1. Generation
The generation program can be permanently stored on EPROM. The
program can be executed using the INTERRUPT key and on pressing
the interrupt key each time, the tones of different frequencies are
generated one by one.
For generation of each tone, the processor determines the digital
signal using function approximation technique and output to CODEC.
The CODEC converts the digital signal to analog signal, which is
amplified, and output to the speaker.
9. 2. Detection
For detection of DTMF tones, the DTMF detection program is
permanently stored in another EPROM. The tone to be detected is
input to the system through CODEC.
The CODEC digitizes the analog signal and send the digital signal to
ADSP-2105. The processor performs FFT operation on the signal to
determine the frequency spectrum of the signal.
The spectrum is output to CRO through DAC and viewed on the screen
of CRO. From the knowledge of frequency spectrum, the input DTMF
tone can be identified.
APPLICATIONS
DTMF is popular in interactive control applications like
1. Telephone banking
2. Electronic Mail system
3. Interactive Telephone Answering systems
4. Railway Reservation system.
ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP technology
which processes the signal to eliminate unwanted noise and improve
incoming signal
DSP
DSP stands for Digital Signal Processor. DSP chips are widely used in sound
cards, fax machines, modems, cellular phones, high-capacity hard disks and
digital TVs. DSP chips are used in sound cards for recording and playback and
speech synthesis. Other audio uses are amplifiers that simulate concert halls
and surround-sound effects for music and home theater
Digital Signal Processing uses mathmatics to operate on a digital signal
(such as a digital audio stream) to generate some type of altered output.
DSP is used heavily in software and hardware effects processing.
DSP chips are found on an increasing number of sound cards to provide
extra audio processing power and help relieve the computers CPU of this
type of work, much like a 3D graphics accelerator would for rendering 3D
graphics
10. FFT/ SPECTRUM ANALYSER/
HARMONIC ANALYSER / FREQUENCY
MEASUREMENT
The aim of the project is to develop a low cost spectrum analyser
using the DSP processor ADSP. The spectrum can be viewed on the
CRO.
Principle
Any analog signal is a mixture of a number of sinusoidal signals of various
frequencies. The various sinusoidal component frequencies of a signal is
called a spectrum.
A sinusoidal signal is a complex quantity and so it has magnitude and
phase. Hence frequency spectrum consists of magnitude plot and phase
plot. In order to detect the presence of a frequency component, it is
sufficient if we obtain the magnitude spectrum alone.
Hence it is decided to compute the magnitude spectrum using ADSP
processor. The processor performs a FFT operation using radix - 4 FFT
algorithm to determine the magnitude spectrum of the signal.
DSP
DSP stands for Digital Signal Processor. DSP chips are widely used in sound
cards, fax machines, modems, cellular phones, high-capacity hard disks and
digital TVs.
DSP chips are used in sound cards for recording and playback and speech
synthesis. Other audio uses are amplifiers that simulate concert halls and
surround-sound effects for music and home theater
Digital Signal Processing uses mathmatics to operate on a digital signal
(such as a digital audio stream) to generate some type of altered output.
DSP is used heavily in software and hardware effects processing.
DSP chips are found on an increasing number of sound cards to provide
extra audio processing power and help relieve the computers CPU of this
type of work, much like a 3D graphics accelerator would for rendering 3D
graphics
11. Hardware
The spectrum analyser system consists of ADSP as CPU, EPROM, RAM,
CODEC and AMPLIFIER. The optional hardware includes serial Input port
and RS 232 level converter for interfacing with PC. Another optional
hardware includes 8031 based waveform generator.
The PC interface can be used to download the object codes of the
program from the PC. The analog signal whose spectrum has to be
estimated is fed to CODEC through MIC or a function generator
(Oscillator).
The CODEC digitize the analog signal and send to ADSP which performs
FFT on the digital signal. The processor output the result of FFT to
CODEC which converts the digital signal to analog. The analog signal is
amplified and displayed on the CRO. The block diagram of the system is
shown in fig.1.
The system can access the analog signal in the frequency range of 0 to
3kHz. The spectrums can be viewed as a voltage spike on the CRO
screen.
For measuring the frequency, a calibration pulse is output by ADSP which
indicates the start of the frequency scale. The divisions on the CRO
screen can be calibrated using a known single frequency signal.
12. FIR FILTER DESIGN USING ADSP
AIM
The aim of this project is to design FIR filter and to implement the
algorithm using ADSP Processor. The system has four selectable
band pass filters, which is used to modify the voice/music.
HARDWARE
The FIR filter system consists of a DSP microprocessor ADSP
CODEC, EPROM, RAM, Amplifier, Mic and speaker.
The CODEC has been interfaced to ADSP processor through its
serial port.
In this system additional serial port has been developed using buffer
and latch to provide serial communication with PC serial port.
The TTL logic levels of serial port are converted to RS-232 level
using level converter, so that the system can directly communicate
with the standard serial port (com1/com2) of Personal Computer
(PC).
SOFTWARE
The system software and filter algorithm are developed in ADSP
assembly language using PC.
The assembly language programs are compiled using ASM21
assembler and converted to machine code which are either
permanently stored in EPROM or downloaded to the ADSP system
through PC serial interface.
FUNCTIONING
The analog input from the microphone is fed to CODEC. The ADSP
reads the digital signal from CODEC, performs filtering operation,
and then output the processed signal back to CODEC.
The CODEC converts the digital signal back to analog and this
analog signal is fed to the speaker. The desired band pass filter can
be selected by using the interrupt key.
13. APPLICATIONS
We can implement the following operations on the voice input
1. Filtering the voice on various bands
2. Changing the nature of voice using filtering
ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP
technology which processes the signal to eliminate unwanted noise
and improve incoming signal
DSP
DSP stands for Digital Signal Processor. DSP chips are widely used
in sound cards, fax machines, modems, cellular phones, high-
capacity hard disks and digital TVs
DSP chips are used in sound cards for recording and playback and
speech synthesis. Other audio uses are amplifiers that simulate
concert halls and surround-sound effects for music and home theater
Digital Signal Processing uses mathmatics to operate on a digital
signal (such as a digital audio stream) to generate some type of
altered output. DSP is used heavily in software and hardware effects
processing.
DSP chips are found on an increasing number of sound cards to
provide extra audio processing power and help relieve the computers
CPU of this type of work, much like a 3D graphics accelerator would
for rendering 3D graphics
15. FUNCTION GENERATOR
The aim of the project is to develop a high precision, function generator
using DSP processor ADSP. The DSP processors are capable of
generating high precision waveforms.
In digital means of generation there is no drift in the generated
waveforms but the drift is inherent in analog systems due to
temperature coefficient of the components.
ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP
technology which processes the signal to eliminate unwanted noise and
improve incoming signal
DSP
DSP stands for Digital Signal Processor. DSP chips are widely used in
sound cards, fax machines, modems, cellular phones, high-capacity
hard disks and digital TVs
DSP chips are used in sound cards for recording and playback and
speech synthesis. Other audio uses are amplifiers that simulate concert
halls and surround-sound effects for music and home theater
Digital Signal Processing uses mathmatics to operate on a digital signal
(such as a digital audio stream) to generate some type of altered output.
DSP is used heavily in software and hardware effects processing.
DSP chips are found on an increasing number of sound cards to provide
extra audio processing power and help relieve the computers CPU of
this type of work, much like a 3D graphics accelerator would for
rendering 3D graphics
PRINCIPLE
Any signal to be generated can be represented by a mathematical
equation and it will be a function of the frequency of the desired signal.
For a given frequency, the function can be evaluated at finite number of
points and the signal can be represented as a set of data. These data
can be output to a DAC to generate the required analog signal.
16. The digital function generator using ADSP has the following
advantages.
1. Precise waveform output.
2. No drift in output due to temperature variations of the
component.
3. Any special type of waveform can be implemented.
HARDWARE
The digital function generator consists of ADSP as CPU, EPROM, RAM,
DAC and Amplifiers. The optional hardware includes PC interface using
serial Input port and level converter. The Input port is implemented
using the buffer
If PC interface is provided, the program for generation of waveform can
be downloaded from PC. When PC interface is not available, the
program can be permanently stored in EPROM.
The program can be executed using the INTERRUPT key. When
interrupt key is pressed the ADSP starts generating the digital waveform
which is output to DAC to convert the digital signal to analog signal.
The analog signal can then be viewed on the CRO.
17. GRAPHICS ENGINE DESIGN ADSP
ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP
technology which processes the signal to eliminate unwanted noise
and improve incoming signal
DSP
DSP stands for Digital Signal Processor. DSP chips are widely used
in sound cards, fax machines, modems, cellular phones, high-
capacity hard disks and digital TVs
DSP chips are used in sound cards for recording and playback and
speech synthesis. Other audio uses are amplifiers that simulate
concert halls and surround-sound effects for music and home
theater
Digital Signal Processing uses mathmatics to operate on a digital
signal (such as a digital audio stream) to generate some type of
altered output. DSP is used heavily in software and hardware effects
processing.
DSP chips are found on an increasing number of sound cards to
provide extra audio processing power and help relieve the
computers CPU of this type of work, much like a 3D graphics
accelerator would for rendering 3D graphics
The objective of this project is to develop a microcomputer system to
generate various complex geometric models, symbols, images etc.
using line drawings. The system is proposed to be developed using the
DSP microcomputer ADSP.
Any complex symbol or image can be constructed using dots and lines
or curves joining the dots. This forms the basic principle of graphics
generation.
For creation or generation of any object, the object has to be defined by
dots and lines joining the dots in a three-dimensional space consisting of
x, y and z axes. These line data, point data (reference data) are used by
the assembly language program developed using ADSP instruction set
to generate the required object.
18. HARDWARE
The graphics engine has been designed in this project using ADSP as
CPU. The system consists of ADSP, EPROM, RAM, PC interface,
Buffer, DAC and amplifiers.
The PC interface has been developed using Serial I/O port and RS232
level converter. The output of DACS can be sent to 2 channels of CRO
to view the generated image on the CRO Screen.
FUNCTIONING
The line data and source data is downloaded from the PC to the ADSP
processor.
On pressing the IRQ2 switch on the kit the object that is created using
line data and source data can be viewed in various mode of rotation. The
zoomed object can also be viewed.
Applications
The concept can be used for
1. Video games
2. Ray tracking
3. Three - dimensional animation
4. Shadow casting
5. Hidden line elimination
20. IMAGE PROCESSING SYSTEM ADSP
TWO DIMENSIONAL FILTERS
BASICS
Image processing is a visual task. An image consists of two-dimensional
array of numbers. Image processing often involves computation on large
matrices that represents digitized images.
Each element of the array represents a pixel of the image; its location in
the array corresponds to its location in the image and its value
determines the shading of the pixel.
Image processing involves processing or altering an existing image in an
desired manner.
The first step is obtaining an image with image data this is achieved
through a stand-alone application program with CIPS. (C image
processing system).
ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP
technology which processes the signal to eliminate unwanted noise
and improve incoming signal
DSP
DSP stands for Digital Signal Processor. DSP chips are widely used
in sound cards, fax machines, modems, cellular phones, high-
capacity hard disks and digital TVs
DSP chips are used in sound cards for recording and playback and
speech synthesis. Other audio uses are amplifiers that simulate
concert halls and surround-sound effects for music and home
theater
Digital Signal Processing uses mathmatics to operate on a digital
signal (such as a digital audio stream) to generate some type of
altered output. DSP is used heavily in software and hardware effects
processing.
21. DSP chips are found on an increasing number of sound cards to
provide extra audio processing power and help relieve the
computers CPU of this type of work, much like a 3D graphics
accelerator would for rendering 3D graphics
HARDWARE
This project is proposed to develop an efficient hardware to implement
the “Image Processing” algorithm.
The hardware required for image processing system have been
implemented using powerful DSP processor ADSP.
The image processing systems consists of ADSP, CODEC, EPROM,
RAM serial port and one level converter.
FUNCTIONING
The image data of the image to be processed is downloaded from the
PC to the ADSP.
The image data from the PC is processed in the ADSP processor (either
filtering or edge detection process) and than the kit on reset, the
processed image can be viewed on the VDU.
APPLICATIONS
Image processing is popular in applications like
1. Remote sensing via satellites
2. Radar
3. Sonar
23. NOISE/ ECHO CANCELLOR
NOISE/ ECHO CANCELLOR
NOISE/ ECHO CANCELLOR
NOISE/ ECHO CANCELLOR
AIM
The aim of the project is to develop an adaptive filter to eliminate
echo/noise .The adaptive filter is implemented in ADSP based system.
THEORY
Normally, in FIR filter, the filter coefficients are constant. But in the
adaptive FIR filters, the filter coefficients will be adjusted or adapt itself
to minimize the errors.
Thus when we employ adaptive filter for echo/noise cancellation, the
FIR filter coefficients are adjusted in every cycle to remove the
echo/noise from the input. In this project Least Mean Square (LMS)
algorithm is used for adaptive filter.
HARDWARE
The physical system consists of a DSP microprocessor ADSP, CODEC,
EPROM, RAM, Amplifiers, Mic, and Speaker. The CODEC has been
interfaced to ADSP processor through its serial port.
In this system additional serial port has been developed using the buffer
and latch to provide serial communication with PC serial port.
The TTL logic levels of serial port are converted to RS-232 logic levels
using converters so that the system can directly communicate with the
standard serial port (com1/com2) of the Personal Computer (PC).
SOFTWARE
The system software and the adaptive filter LMS algorithm are
developed in ADSP assembly language using PC.
The Assembly language programs are compiled using ASM21
Assembler and converted to machine code which are either
permanently stored in EPROM or downloaded to the ADSP system
through PC serial interface.
24. FUNCTIONING
The analog input signal from the mic are amplified and fed to the
CODEC. The CODEC converts the analog signal into digital and
transfers the data to DSP microprocessor.
In order to demonstrate echo/noise cancellation, first processor
generates an echo/noise and mix with the input signal and the resultant
signal is output to speaker.
Then using the interrupt adaptive filter algorithm is enabled and the
combined signal is processed by the adaptive filter and the filtered
signal is output through speaker. We can observe the gradual
elimination of echo/noise.
APPLICATIONS
The Adaptive filter is widely used in applications like
1. Digital audio
2. Digital graphical equalizer
3. Noise removal in transmission channels
4. High speed modem
5. Echo cancellation in transmission channels.
ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP technology
which processes the signal to eliminate unwanted noise and improve
incoming signal
DSP
DSP stands for Digital Signal Processor. DSP chips are widely used in sound
cards, fax machines, modems, cellular phones, high-capacity hard disks and
digital TVs. DSP chips are used in sound cards for recording and playback
and speech synthesis. Other audio uses are amplifiers that simulate concert
halls and surround-sound effects for music and home theater
Digital Signal Processing uses mathmatics to operate on a digital signal (such
as a digital audio stream) to generate some type of altered output. DSP is
used heavily in software and hardware effects processing.
DSP chips are found on an increasing number of sound cards to provide extra
audio processing power and help relieve the computers CPU of this type of
work, much like a 3D graphics accelerator would for rendering 3D graphics
26. SPEECH COMPRESSION AND
SPEECH COMPRESSION AND
SPEECH COMPRESSION AND
SPEECH COMPRESSION AND
DECOMPRESSION USING ADPCM
DECOMPRESSION USING ADPCM
DECOMPRESSION USING ADPCM
DECOMPRESSION USING ADPCM
TECHNIQUE
TECHNIQUE
TECHNIQUE
TECHNIQUE
BASICS
Speech coding may be defined as a digital representation of the
speech signal that provides efficient storage, transmission, recovery
and faithful reconstruction of the original speech.
The speech compression is achieved by representing each sample of
digitized data by lesser number of bits. For maintaining the voice
quality the speech sample has to be represented by 13 to 16 bits.
In compression techniques the 13 to 16 bits data is represented by
an equivalent 4 or 8 bit data. In decompression techniques the
compressed data is converted back to original data. One of the
important requirement in these techniques is that the voice quality
has to be maintained.
HARDWARE
This project is proposed to develop an efficient hardware to
implement the powerful and versatile ADPCM speech compression
and decompression algorithm.
The hardware required for speech compression and decompression
have been developed using powerful DSP processor ADSP-2105.
The speech processing system consists of ADSP - 2105, CODEC,
EPROM, RAM, Amplifier sections, mike and speakers.
FUNCTIONING
The system is ready to accept speech signal once it is reset. The
speech segment to be compressed is fed as input through
microphone. The analog speech signal is digitized by CODEC,
compressed by ADSP-2105 and stored in RAM.
The decompression process can be started by interrupting the
processor.
27. When the processor is interrupted, the information in memory is
fetched by the processor and decompressed and is then fed to
CODEC. The CODEC converts the digital signal to analog signal.
The analog signal is amplified and output through the speaker.
FEATURES
The speech compression and decompression techniques are
implemented in cellular phones, voice mail transmission systems and
speech recognition system.
What is ADPCM
Adaptive delta pulse code modulation. An audio compression
algorithm for digital audio based on describing level differences
between adjacent samples
Adaptive Differential Pulse Code Modulation is an audio encoding
compression technique that encodes the difference between the
predicted value of the signal instead of the absolute value of the
original waveform so that the compression efficiency is improved.
This difference is usually small and can thus be encoded in fewer bits
than the sample itself. ADPCM is used in PC sound cards, on CD-i
and CD-ROM XA discs
CODEC
Codec is an abbreviation for Coder-Decoder. It's an analog-to-digital
(A/D) and digital-to-analog (D/A) converter for translating the signals
from the outside world to digital, and back again
ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP
technology which processes the signal to eliminate unwanted noise
and improve incoming signal
28. DSP
DSP stands for Digital Signal Processor. DSP chips are widely used
in sound cards, fax machines, modems, cellular phones, high-
capacity hard disks and digital TVs
DSP chips are used in sound cards for recording and playback and
speech synthesis. Other audio uses are amplifiers that simulate
concert halls and surround-sound effects for music and home theater
Digital Signal Processing uses mathmatics to operate on a digital
signal (such as a digital audio stream) to generate some type of
altered output. DSP is used heavily in software and hardware effects
processing.
DSP chips are found on an increasing number of sound cards to
provide extra audio processing power and help relieve the computers
CPU of this type of work, much like a 3D graphics accelerator would
for rendering 3D graphics
29. VOICE COMPERSION USING ADSP
What is Voice Compression
The conversion of an analog voice signal into a digital signal using minimum
bandwidth, Process by which the high statistical correlation between
consecutive voice samples is used to create a variable quantizing scale.
ADPCM can encode analog voice samples into high - toll - quality digital
signals
DSP Processor are widely used for analog signal processing such as
filtering, compression of voice signal and image processing. The processor
has powerful instruction sets and most of the instructions are one cycle
execution. So that the result can be obtained much faster and efficient,
which is required for Analog signal processing.
In this project, we are using ADSP (DSP) processor for voice
compression and retrieving.
This voice signal is picked up by microphone and it is amplified by the Pre-
Amplifier to 0-5V level. The amplified signal fed to CODEC. The CODEC has
an ADC (Analog Digital Converter), which receives the signal from pre-amp
and converts it in to Digital data.
The Converted digital data is encoded in serial format and transmitted to
DSP processor by the CODEC. The CODEC and DSP processor are linked
by synchronized serial port.
The processor has two memory blocks externally, Data memory and Boot
memory. On power on reset the program from the Boot memory (which is
developed and stored in EPROM) is loaded to the internal Program memory
of the processor. After the completing loading sequence it starts executing.
The program is developed such that to receive the data from CODEC and
compress it using Linear Predictive Coding (LPC).
The compressed data are stored in external data memory (DM). When the
IRQ pin is asserted the data from DM is read and expanded. The expanded
data is transmitted to the serial Port (to CODEC)
The CODEC receives the data and decodes it. The decoded data is fed to
DAC (which is build-in CODEC). And the DAC reproduces the exact analog
signal and amplified by the Audio Power Amplifier
30. What is ADPCM
Adaptive delta pulse code modulation. An audio compression algorithm for
digital audio based on describing level differences between adjacent
samples
Adaptive Differential Pulse Code Modulation is an audio encoding
compression technique that encodes the difference between the predicted
value of the signal instead of the absolute value of the original waveform so
that the compression efficiency is improved.
This difference is usually small and can thus be encoded in fewer bits than
the sample itself. ADPCM is used in PC sound cards, on CD-i and CD-ROM
XA discs
CODEC
Codec is an abbreviation for Coder-Decoder. It's an analog-to-digital (A/D)
and digital-to-analog (D/A) converter for translating the signals from the
outside world to digital, and back again
ADSP
Adaptive Digital Signal Processing; exclusive to SGC, a DSP technology
which processes the signal to eliminate unwanted noise and improve
incoming signal
DSP
DSP stands for Digital Signal Processor. DSP chips are widely used in
sound cards, fax machines, modems, cellular phones, high-capacity hard
disks and digital TVs
DSP chips are used in sound cards for recording and playback and speech
synthesis. Other audio uses are amplifiers that simulate concert halls and
surround-sound effects for music and home theater
Digital Signal Processing uses mathmatics to operate on a digital signal
(such as a digital audio stream) to generate some type of altered output.
DSP is used heavily in software and hardware effects processing.
DSP chips are found on an increasing number of sound cards to provide
extra audio processing power and help relieve the computers CPU of this
type of work, much like a 3D graphics accelerator would for rendering 3D
graphics
31. The block diagram is shown below.
DATA
MEMORY
BOOT
MEMORY
CODEC
ADSP
2105
DSP
PRE
AMP
MIC
PWR
AMP
SPK