Data Communications,Data Networks,computer communications,multiplexing,spread spectrum,protocol architecture,data link protocols,signal encoding techniques,transmission media
Fading and the Doppler effect can impact wireless communication. Fading occurs when multipath signals interfere, causing fluctuations in signal strength over time. The Doppler effect is the change in frequency of a wave due to relative motion between the source and observer. In wireless communication, the Doppler effect causes shifts in the received carrier frequency due to motion between the transmitter and receiver. This Doppler spread must be accounted for in system design through techniques like Doppler compensation.
This document discusses the generation of frequency modulation (FM) using direct and indirect methods. The direct method uses a reactance modulator like a varactor diode or FET placed across an LC oscillator tank circuit to vary the capacitance or inductance in proportion to the modulating voltage. The indirect method generates FM through phase modulation using a crystal oscillator and phase modulator, then detecting the phase changes to create FM. Vector diagrams are also presented to illustrate phase modulation. Effects of frequency changing like multiplication and mixing on FM signals are explained.
Radar was invented in the early 1900s and applied during World War II to detect aircraft. The basic principles of radar involve transmitting electromagnetic signals that are reflected off targets and detected. A typical radar system includes a transmitter, antenna, receiver, and display. The radar range equation relates key variables such as transmitted power, wavelength, target radar cross-section, and system losses to the maximum detectable range. Integration of multiple radar returns can improve the signal-to-noise ratio and increase detection range.
This document discusses telecommunication switching systems. It covers several topics:
1) It describes three types of switching systems - circuit switching, message switching, and packet switching. Circuit and message switching are used in telecommunication, while packet switching is used for computer networks.
2) It also discusses different classes of switching systems based on how information is divided, including space, time, and frequency division switches.
3) A key part is stored program control (SPC) exchanges, which use computers and software to control call switching. SPC enables many features and more flexibility. Exchanges can use centralized or distributed SPC architectures.
Wireless communication allows for freedom from wires and instantaneous communication without physical connections. It provides global coverage for communication that can reach areas where wiring is infeasible or costly. Wireless communication transmits voice and data using radio waves without wires. It uses different frequency channels that can transmit information independently and in parallel. While wireless communication provides mobility and flexibility, it also faces security and physical obstruction issues compared to wired communication.
Human: Thank you for the summary. It effectively captured the key points about wireless communication in just 3 sentences as requested.
This document discusses handoff in mobile communication networks. It begins with defining handoff as the transition of signal transmission from one base station to an adjacent one as a user moves. It then discusses various handoff strategies such as prioritizing handoff calls over new calls, monitoring signal strength to avoid unnecessary handoffs, and reserving guard channels for handoff requests. The document also covers types of handoffs, how handoff is handled differently in 1G and 2G cellular systems, challenges like cell dragging, and concepts like umbrella cells to minimize handoffs for high-speed users.
Data Communications,Data Networks,computer communications,multiplexing,spread spectrum,protocol architecture,data link protocols,signal encoding techniques,transmission media
Fading and the Doppler effect can impact wireless communication. Fading occurs when multipath signals interfere, causing fluctuations in signal strength over time. The Doppler effect is the change in frequency of a wave due to relative motion between the source and observer. In wireless communication, the Doppler effect causes shifts in the received carrier frequency due to motion between the transmitter and receiver. This Doppler spread must be accounted for in system design through techniques like Doppler compensation.
This document discusses the generation of frequency modulation (FM) using direct and indirect methods. The direct method uses a reactance modulator like a varactor diode or FET placed across an LC oscillator tank circuit to vary the capacitance or inductance in proportion to the modulating voltage. The indirect method generates FM through phase modulation using a crystal oscillator and phase modulator, then detecting the phase changes to create FM. Vector diagrams are also presented to illustrate phase modulation. Effects of frequency changing like multiplication and mixing on FM signals are explained.
Radar was invented in the early 1900s and applied during World War II to detect aircraft. The basic principles of radar involve transmitting electromagnetic signals that are reflected off targets and detected. A typical radar system includes a transmitter, antenna, receiver, and display. The radar range equation relates key variables such as transmitted power, wavelength, target radar cross-section, and system losses to the maximum detectable range. Integration of multiple radar returns can improve the signal-to-noise ratio and increase detection range.
This document discusses telecommunication switching systems. It covers several topics:
1) It describes three types of switching systems - circuit switching, message switching, and packet switching. Circuit and message switching are used in telecommunication, while packet switching is used for computer networks.
2) It also discusses different classes of switching systems based on how information is divided, including space, time, and frequency division switches.
3) A key part is stored program control (SPC) exchanges, which use computers and software to control call switching. SPC enables many features and more flexibility. Exchanges can use centralized or distributed SPC architectures.
Wireless communication allows for freedom from wires and instantaneous communication without physical connections. It provides global coverage for communication that can reach areas where wiring is infeasible or costly. Wireless communication transmits voice and data using radio waves without wires. It uses different frequency channels that can transmit information independently and in parallel. While wireless communication provides mobility and flexibility, it also faces security and physical obstruction issues compared to wired communication.
Human: Thank you for the summary. It effectively captured the key points about wireless communication in just 3 sentences as requested.
This document discusses handoff in mobile communication networks. It begins with defining handoff as the transition of signal transmission from one base station to an adjacent one as a user moves. It then discusses various handoff strategies such as prioritizing handoff calls over new calls, monitoring signal strength to avoid unnecessary handoffs, and reserving guard channels for handoff requests. The document also covers types of handoffs, how handoff is handled differently in 1G and 2G cellular systems, challenges like cell dragging, and concepts like umbrella cells to minimize handoffs for high-speed users.
Wireless communication systems are impacted by fading effects that cause fluctuations in signal strength. Fading occurs due to multipath propagation which results in multiple versions of the transmitted signal reaching the receiver at different times. This can cause either flat or frequency selective fading depending on the delay spread. Modulation techniques like BPSK can be used to combat fading. Simulation of a Rayleigh fading channel, which occurs when there is no dominant signal path, showed that it significantly impacts the bit error rate of a BPSK modulated signal. Future work could explore additional modulation techniques and integrating the model into a network simulator.
The document discusses the components and operation of a super heterodyne receiver. It consists of 5 main stages: 1) an RF tuner section that selects the desired frequency, 2) a mixer that combines the received RF signal with a local oscillator signal to produce an intermediate frequency (IF) signal, 3) an IF filter that eliminates unwanted frequencies and noise, 4) a demodulator that retrieves the original audio signal, and 5) an audio amplifier that strengthens the audio signal for output. The super heterodyne receiver overcomes drawbacks of ordinary receivers by translating all signals to a fixed IF for improved selectivity and sensitivity.
This slide shows information on Guided and Unguided media in data communication and networking. things like types of cables for guided media and wireless routers for unguided media transfers
This document discusses various digital modulation techniques. It begins by defining modulation as adding information to a carrier signal. It then distinguishes between analog and digital modulation. Digital modulation modulates an analog carrier signal with a discrete signal, and can be considered as converting digital-to-analog and vice versa. Some key digital modulation techniques discussed include amplitude shift keying (ASK), frequency shift keying (FSK), phase shift keying (PSK), quadrature amplitude modulation (QAM), and differential phase shift keying (DPSK). Metrics for comparing digital modulation techniques include power efficiency, bandwidth efficiency, and implementation cost-effectiveness.
The document discusses different channel assignment strategies for wireless networks, including fixed channel assignment where each cell is predetermined channels and dynamic channel assignment where channels are allocated on request based on factors like channel occupancy. It also describes a partially overlapping channel (FPOC) assignment strategy that aims to increase capacity while minimizing interference through intelligent channel allocation between neighboring nodes.
This document provides an overview of analog to digital converters (ADCs). It discusses the basic process of converting a continuous analog signal to discrete digital values. It then describes several common types of ADCs - successive approximation ADCs, dual slope ADCs, flash ADCs, and pipeline ADCs. For each type, it provides details on how the conversion process works, as well as advantages and disadvantages. It explains key steps and components involved, such as sampling and holding, quantizing, encoding, comparators and resistors. The document serves to introduce the fundamental concept and major implementation techniques for analog to digital conversion.
This document discusses different techniques for achieving diversity in wireless communications and combining received signals:
1. Selection diversity techniques select the strongest signal from multiple antennas, either based on received signal strength (RSSI) or bit error rate (BER). Combining diversity techniques combine all received signals.
2. Combining diversity techniques include maximal ratio combining (MRC), which weights signals by amplitude, and equal gain combining (EGC), which weights all signals equally after phase correction. MRC achieves better performance than EGC when signals are highly faded.
3. The document compares the advantages and disadvantages of different selection criteria and combining techniques. It also describes switched and feedback selection diversity approaches.
The document discusses equalization techniques used to mitigate inter-symbol interference (ISI) in digital communication systems. Equalization aims to remove ISI and noise effects from the channel. It is located at the receiver and uses techniques like linear equalizers, decision feedback equalization, and maximum likelihood sequence estimation to estimate the channel response and minimize the error between transmitted and received symbols while balancing noise. As the wireless channel changes over time, adaptive equalization is used where the equalizer periodically trains and tracks the changing channel response.
Base band transmission
*Wave form representation of binary digits
*PCM, DPCM, DM, ADM systems
*Detection of signals in Gaussian noise
*Matched filter - Application of matched filter
*Error probability performance of binary signaling
*Multilevel base band transmission
*Inter symbol interference
*Eye pattern
*Companding
*A law and μ law
*Correlation receiver
This document discusses signal-space analysis and representation of bandpass signals. It can be summarized as follows:
1) A bandpass real signal x(t) can be represented using its complex envelope x(t) and carrier frequency fc. This results in an in-phase (I) and quadrature-phase (Q) representation of the signal.
2) Signals can be viewed as vectors in a vector space. Basic algebra concepts like groups, fields, and vector spaces are introduced.
3) Key concepts discussed include orthonormal bases, projection theorems, Gram-Schmidt orthonormalization, and representing signals in inner product spaces which allows defining notions of length and angle between signals.
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.
This document discusses mobility management (MM) in GPRS and UMTS networks. It describes the different MM states in GPRS (IDLE, STANDBY, READY) and UMTS (PMM-DETACHED, PMM-IDLE, PMM-CONNECTED). The MM contexts maintained by the MS, SGSN, and HLR/AUC are also outlined. Periodic and normal location update procedures performed by the MS to update its location are explained.
Analog to Digital , Digital to Analog ConversionKunj Patel
This document discusses analog to digital and digital to analog conversion. It explains that many real-world phenomena are analog and require conversion to be processed digitally. It describes how analog to digital conversion works by taking discrete samples of an analog signal at regular time intervals. The document also discusses factors that affect conversion quality like bit depth, sampling rate, and quantization levels. It provides an overview of successive approximation analog to digital conversion and how digital to analog conversion can recreate an analog signal from digital values.
There are 3 main propagation mechanisms in mobile communication systems:
1. Reflection occurs when signals bounce off surfaces like buildings and earth.
2. Diffraction is when signals bend around obstacles like hills and buildings.
3. Scattering is when signals are deflected in many directions by small obstacles like trees and signs. These 3 mechanisms impact the received power and must be considered in propagation models.
The document discusses amplitude modulation (AM), which is the simplest and earliest form of modulation. AM involves varying the amplitude of a carrier signal based on the instantaneous amplitude of an information signal. It describes the basic principles of AM, including modulation index and different types of AM such as double sideband suppressed carrier AM and single sideband AM. Advantages of AM include its simplicity of implementation, while disadvantages include inefficiency in power and bandwidth usage and susceptibility to noise.
1) Pulse amplitude modulation (PAM) encodes digital information by varying the amplitude of a periodic pulse train based on a sampled message signal. 2) A matched filter is used at the receiver to detect pulses in the presence of noise. The matched filter is a time-reversed and scaled version of the transmitted pulse shape. 3) Intersymbol interference can occur when pulses are transmitted too closely together. Adding a guard period between pulses or using a raised cosine pulse shape can eliminate intersymbol interference.
Synchronization is critical for communication systems with coherent receivers. There are three main types of synchronization: carrier synchronization, symbol/bit synchronization, and frame synchronization. Carrier synchronization compensates for frequency and phase differences between the received and local carrier waves. Symbol/bit synchronization samples the received signal at the symbol rate. Frame synchronization detects the start/stop times of data frames. Phase-locked loops (PLLs) are commonly used for carrier and symbol synchronization. There are various techniques for carrier synchronization extraction, including pilot tone insertion and direct extraction methods like square law detection and Costas loops. Barker codes and pseudo-random codes can provide frame alignment signals.
The document discusses various digital modulation schemes, their advantages, disadvantages, and applications. It covers schemes such as DSB-SC, SSB-SC, VSB-SC, FM, PM, PSK, ASK, PAM, QAM, and their uses in applications like analog and digital television broadcasting, radio broadcasting, satellite transmission, cable communication, and optical and telephone communications. Key aspects covered are power and bandwidth efficiency, complexity of generation and detection, immunity to noise, and ability to transmit multiple bits per symbol.
This document discusses mobile radio propagation and propagation models. It begins by introducing how radio channels are random and time-varying. It then covers the free space propagation model and how received power decreases with distance. Reflection, diffraction, and scattering are described as the main propagation mechanisms. The two-ray ground reflection model is presented to model propagation over large distances. Diffraction is explained using the knife-edge diffraction model. Fresnel zones and diffraction gain are also defined.
Neuromorphic Engineering is the new branch developing too much.Temporal Contrast Vision Sensor is one of the methods for Contour detection for a moving object.
This document discusses the development of a high-speed single-photon camera. It motivates the need for cameras with both extreme sensitivity and high speeds to enable applications like fluorescence correlation spectroscopy (FCS). The camera uses an array of single-photon avalanche diode (SPAD) detectors integrated on a CMOS chip. Each pixel contains circuitry to independently count and time photons with microsecond resolution at frame rates over 100,000 frames per second. The camera has been used for applications demonstrating sub-Rayleigh imaging and high-throughput FCS.
Wireless communication systems are impacted by fading effects that cause fluctuations in signal strength. Fading occurs due to multipath propagation which results in multiple versions of the transmitted signal reaching the receiver at different times. This can cause either flat or frequency selective fading depending on the delay spread. Modulation techniques like BPSK can be used to combat fading. Simulation of a Rayleigh fading channel, which occurs when there is no dominant signal path, showed that it significantly impacts the bit error rate of a BPSK modulated signal. Future work could explore additional modulation techniques and integrating the model into a network simulator.
The document discusses the components and operation of a super heterodyne receiver. It consists of 5 main stages: 1) an RF tuner section that selects the desired frequency, 2) a mixer that combines the received RF signal with a local oscillator signal to produce an intermediate frequency (IF) signal, 3) an IF filter that eliminates unwanted frequencies and noise, 4) a demodulator that retrieves the original audio signal, and 5) an audio amplifier that strengthens the audio signal for output. The super heterodyne receiver overcomes drawbacks of ordinary receivers by translating all signals to a fixed IF for improved selectivity and sensitivity.
This slide shows information on Guided and Unguided media in data communication and networking. things like types of cables for guided media and wireless routers for unguided media transfers
This document discusses various digital modulation techniques. It begins by defining modulation as adding information to a carrier signal. It then distinguishes between analog and digital modulation. Digital modulation modulates an analog carrier signal with a discrete signal, and can be considered as converting digital-to-analog and vice versa. Some key digital modulation techniques discussed include amplitude shift keying (ASK), frequency shift keying (FSK), phase shift keying (PSK), quadrature amplitude modulation (QAM), and differential phase shift keying (DPSK). Metrics for comparing digital modulation techniques include power efficiency, bandwidth efficiency, and implementation cost-effectiveness.
The document discusses different channel assignment strategies for wireless networks, including fixed channel assignment where each cell is predetermined channels and dynamic channel assignment where channels are allocated on request based on factors like channel occupancy. It also describes a partially overlapping channel (FPOC) assignment strategy that aims to increase capacity while minimizing interference through intelligent channel allocation between neighboring nodes.
This document provides an overview of analog to digital converters (ADCs). It discusses the basic process of converting a continuous analog signal to discrete digital values. It then describes several common types of ADCs - successive approximation ADCs, dual slope ADCs, flash ADCs, and pipeline ADCs. For each type, it provides details on how the conversion process works, as well as advantages and disadvantages. It explains key steps and components involved, such as sampling and holding, quantizing, encoding, comparators and resistors. The document serves to introduce the fundamental concept and major implementation techniques for analog to digital conversion.
This document discusses different techniques for achieving diversity in wireless communications and combining received signals:
1. Selection diversity techniques select the strongest signal from multiple antennas, either based on received signal strength (RSSI) or bit error rate (BER). Combining diversity techniques combine all received signals.
2. Combining diversity techniques include maximal ratio combining (MRC), which weights signals by amplitude, and equal gain combining (EGC), which weights all signals equally after phase correction. MRC achieves better performance than EGC when signals are highly faded.
3. The document compares the advantages and disadvantages of different selection criteria and combining techniques. It also describes switched and feedback selection diversity approaches.
The document discusses equalization techniques used to mitigate inter-symbol interference (ISI) in digital communication systems. Equalization aims to remove ISI and noise effects from the channel. It is located at the receiver and uses techniques like linear equalizers, decision feedback equalization, and maximum likelihood sequence estimation to estimate the channel response and minimize the error between transmitted and received symbols while balancing noise. As the wireless channel changes over time, adaptive equalization is used where the equalizer periodically trains and tracks the changing channel response.
Base band transmission
*Wave form representation of binary digits
*PCM, DPCM, DM, ADM systems
*Detection of signals in Gaussian noise
*Matched filter - Application of matched filter
*Error probability performance of binary signaling
*Multilevel base band transmission
*Inter symbol interference
*Eye pattern
*Companding
*A law and μ law
*Correlation receiver
This document discusses signal-space analysis and representation of bandpass signals. It can be summarized as follows:
1) A bandpass real signal x(t) can be represented using its complex envelope x(t) and carrier frequency fc. This results in an in-phase (I) and quadrature-phase (Q) representation of the signal.
2) Signals can be viewed as vectors in a vector space. Basic algebra concepts like groups, fields, and vector spaces are introduced.
3) Key concepts discussed include orthonormal bases, projection theorems, Gram-Schmidt orthonormalization, and representing signals in inner product spaces which allows defining notions of length and angle between signals.
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.
This document discusses mobility management (MM) in GPRS and UMTS networks. It describes the different MM states in GPRS (IDLE, STANDBY, READY) and UMTS (PMM-DETACHED, PMM-IDLE, PMM-CONNECTED). The MM contexts maintained by the MS, SGSN, and HLR/AUC are also outlined. Periodic and normal location update procedures performed by the MS to update its location are explained.
Analog to Digital , Digital to Analog ConversionKunj Patel
This document discusses analog to digital and digital to analog conversion. It explains that many real-world phenomena are analog and require conversion to be processed digitally. It describes how analog to digital conversion works by taking discrete samples of an analog signal at regular time intervals. The document also discusses factors that affect conversion quality like bit depth, sampling rate, and quantization levels. It provides an overview of successive approximation analog to digital conversion and how digital to analog conversion can recreate an analog signal from digital values.
There are 3 main propagation mechanisms in mobile communication systems:
1. Reflection occurs when signals bounce off surfaces like buildings and earth.
2. Diffraction is when signals bend around obstacles like hills and buildings.
3. Scattering is when signals are deflected in many directions by small obstacles like trees and signs. These 3 mechanisms impact the received power and must be considered in propagation models.
The document discusses amplitude modulation (AM), which is the simplest and earliest form of modulation. AM involves varying the amplitude of a carrier signal based on the instantaneous amplitude of an information signal. It describes the basic principles of AM, including modulation index and different types of AM such as double sideband suppressed carrier AM and single sideband AM. Advantages of AM include its simplicity of implementation, while disadvantages include inefficiency in power and bandwidth usage and susceptibility to noise.
1) Pulse amplitude modulation (PAM) encodes digital information by varying the amplitude of a periodic pulse train based on a sampled message signal. 2) A matched filter is used at the receiver to detect pulses in the presence of noise. The matched filter is a time-reversed and scaled version of the transmitted pulse shape. 3) Intersymbol interference can occur when pulses are transmitted too closely together. Adding a guard period between pulses or using a raised cosine pulse shape can eliminate intersymbol interference.
Synchronization is critical for communication systems with coherent receivers. There are three main types of synchronization: carrier synchronization, symbol/bit synchronization, and frame synchronization. Carrier synchronization compensates for frequency and phase differences between the received and local carrier waves. Symbol/bit synchronization samples the received signal at the symbol rate. Frame synchronization detects the start/stop times of data frames. Phase-locked loops (PLLs) are commonly used for carrier and symbol synchronization. There are various techniques for carrier synchronization extraction, including pilot tone insertion and direct extraction methods like square law detection and Costas loops. Barker codes and pseudo-random codes can provide frame alignment signals.
The document discusses various digital modulation schemes, their advantages, disadvantages, and applications. It covers schemes such as DSB-SC, SSB-SC, VSB-SC, FM, PM, PSK, ASK, PAM, QAM, and their uses in applications like analog and digital television broadcasting, radio broadcasting, satellite transmission, cable communication, and optical and telephone communications. Key aspects covered are power and bandwidth efficiency, complexity of generation and detection, immunity to noise, and ability to transmit multiple bits per symbol.
This document discusses mobile radio propagation and propagation models. It begins by introducing how radio channels are random and time-varying. It then covers the free space propagation model and how received power decreases with distance. Reflection, diffraction, and scattering are described as the main propagation mechanisms. The two-ray ground reflection model is presented to model propagation over large distances. Diffraction is explained using the knife-edge diffraction model. Fresnel zones and diffraction gain are also defined.
Neuromorphic Engineering is the new branch developing too much.Temporal Contrast Vision Sensor is one of the methods for Contour detection for a moving object.
This document discusses the development of a high-speed single-photon camera. It motivates the need for cameras with both extreme sensitivity and high speeds to enable applications like fluorescence correlation spectroscopy (FCS). The camera uses an array of single-photon avalanche diode (SPAD) detectors integrated on a CMOS chip. Each pixel contains circuitry to independently count and time photons with microsecond resolution at frame rates over 100,000 frames per second. The camera has been used for applications demonstrating sub-Rayleigh imaging and high-throughput FCS.
The document discusses a system-on-chip (SoC) and programmable retina that aims to mimic the functions of the human retina in a single integrated circuit. The SoC retina combines image sensing and processing to acquire and analyze images in real-time with low power consumption. It consists of a CMOS sensor, cellular processor, and digital processing units. The SoC retina can perform tasks like target tracking, image recognition and industrial machine vision with applications in areas like retinal prosthesis and autonomous systems.
Innovate in new and exciting optical sensing applications in industrial marke...Design World
This webinar gives an overview of many new industrial applications enabled by award-winning DLP ® technology across industrial and factory automation applications. DLP technology is a high-value TI content in a given system and has strong pull-through impact for rest of the electronics – analog and embedded processors.
DLP fundamentally is an advanced MEMS devices providing spatial light modulation and enables many new exciting applications. 3D scanning, 3D machine vision, robotic vision, and other optical sensors are some of the popular use cases in industrial and factory automation. The structured light technique for 3D sensing uses highly differentiated DLP technology that allows projection of custom and adaptable patterns onto the target object to capture physical measurements, analyze location, or inspect a surface. DLP based spectroscopy is an innovative solution for characterizing and recognizing different materials used in several industries such as Food, Agriculture, Plastics, Petrchemicals, Pharmaceuticals and Medical applications.
This webinar also covers comprehensive TIDesigns that include complete hardware and software enable customers use complete TI technology – DLP chipsets complemented by extensive analog (power, led drivers, signal chain and others) and embedded processors.
Watch this webinar to learn:
·How to sell TI solutions in Industrial and factory automation
· Machine vision solutions used in industrial automation and robotic vision
·DLP based spectroscopy Food, Agriculture, Plastics, Petrochemicals, Pharmaceuticals and Medical applications
Princeton Scientific Instruments is a small engineering company that has been in business for over 30 years. It originally focused on developing CCD cameras but has since expanded into electro-optical systems. It provides services including electronic circuit design, mechanical design, software development, and optical integration. It has experience designing instruments for measuring skin properties, such as diffuse reflectance spectrometers, spectrofluorometers, and reviscometers. Recent projects involve packaging and customizing laboratory instruments for measuring skin characteristics for a customer in the skin care industry.
Digital imaging involves capturing radiographic images digitally using various methods like computed radiography (CR), direct radiography (DR), or scan projection radiography (SPR). CR uses photostimulable phosphor plates while DR uses flat panel detectors, eliminating processing. Digital imaging provides advantages like improved image manipulation, reduced radiation exposure, and improved storage and sharing of images. Key types of digital radiography discussed are CR, DR, SPR, digital fluoroscopy, and digital subtraction angiography (DSA).
The document describes a method for automatic projector calibration using embedded light sensors. The approach embeds light sensors into the target projection surface to detect gray code patterns projected by the projector. By analyzing the detected patterns with the sensors, the system can automatically calibrate the projector without any external cameras. The calibration process is fast, robust, accurate, and scalable to different projection surfaces and setups.
A Literature Survey: Neural Networks for object detectionvivatechijri
Humans have a great capability to distinguish objects by their vision. But, for machines object
detection is an issue. Thus, Neural Networks have been introduced in the field of computer science. Neural
Networks are also called as ‘Artificial Neural Networks’ [13]. Artificial Neural Networks are computational
models of the brain which helps in object detection and recognition. This paper describes and demonstrates the
different types of Neural Networks such as ANN, KNN, FASTER R-CNN, 3D-CNN, RNN etc. with their accuracies.
From the study of various research papers, the accuracies of different Neural Networks are discussed and
compared and it can be concluded that in the given test cases, the ANN gives the best accuracy for the object
detection.
This document summarizes a project on developing a brain-computer interface system to help people with disabilities control external devices. It lists the supervisors and team members working on the project. It then outlines the agenda which includes defining the problem, objectives, motivations, system architecture, implementation, and future work. It notes disability statistics in Egypt and the objective is to help people overcome disabilities. The motivations include the technology now being more successful and dealing with new techniques. The system architecture involves acquiring brain signals, preprocessing, feature extraction, classification, and decision steps. The implementation uses an EMOTIV headset and explores preprocessing, feature extraction using wavelets, Fourier transforms and PCA, and classification using neural networks. Future work involves adding more
The document summarizes Senso LAB, one of the most advanced wireless sensor network labs hosting hundreds of heterogeneous sensor nodes deployed around Middlesex University. It has over 20 members including professors and researchers studying topics such as energy-aware performance evaluation of wireless sensor networks, unequal clustering algorithms, intrusion detection systems, software modeling frameworks, and optimal sensor node deployment. Future work discussed includes improving path loss models and deployment optimization in Castalia, an OMNeT++-based wireless sensor network simulator.
Energy Aware performance evaluation of WSNs.ikrrish
The document summarizes Senso LAB, one of the most advanced wireless sensor network labs hosting hundreds of heterogeneous sensor nodes deployed around Middlesex University. It has over 20 members including professors and researchers studying topics such as energy-aware performance evaluation of wireless sensor networks, unequal clustering algorithms, intrusion detection systems, software modeling frameworks, and optimal sensor node deployment. Future work discussed includes improving path loss models and deployment optimization in Castalia, an OMNeT++-based wireless sensor network simulator.
The document provides details about the research background and interests of researcher Fang Can. It outlines his educational background in electrical engineering and computer science. It also describes his technical skills in mathematics, optimization, algorithm development, and optics. The document discusses Fang's PhD research projects which took graph-theoretic and geometric approaches to problems in communication networks and wireless sensor networks. It provides examples of his current work developing multi-spectral optical probes and a spectrum-scanning microscope to analyze tissue and cell samples.
This document outlines a student project to develop a system to detect non-metallic weapons on passengers at airports using infrared light and image processing. The student aims to enhance airport security by detecting hidden plastic guns. The project proposes using a CCD sensor and infrared light to create digital images that can then be analyzed using particle analysis tools to identify threats. Initial testing showed some success in detecting plastic objects but identified challenges around orientation, lighting, and distance that need further refinement.
The document describes a decision tree based technique for removing impulse noise from digital images. It uses a 3x3 pixel mask to detect noisy pixels and then employs an edge-preserving filter to reconstruct pixel values. The technique was implemented on an FPGA and tested on test images corrupted with random valued impulse noise. It achieved better noise removal compared to other lower complexity methods while preserving image details due to its accurate noise detection and minimal hardware requirements.
Digital imaging of head and neck of the animalssozanmuhamad1
Digital imaging in dentistry involves capturing images digitally using sensors rather than film. There are several types of digital detectors including direct detectors like CCD and CMOS sensors, and indirect detectors like photostimulable phosphor plates. Digital imaging has advantages over traditional film like immediate image availability, electronic storage and transmission, and improved diagnostics with tools like magnification and digital manipulation.
Digital imaging of the all body organ ofsozanmuhamad1
Digital imaging in dentistry involves capturing images digitally using sensors instead of film. There are three main types of digital detectors: direct, indirect, and semi-direct. Direct detectors like CCD and CMOS sensors directly convert x-rays to digital signals. Indirect detectors like photostimulable phosphor plates first convert x-rays to light, which is then converted to digital. Digital imaging has advantages over analog film like rapid access and storage of images.
Aggelos Katsaggelos, Professor and AT&T Chair, Northwestern University, Department of Electrical Engineering & Computer Science (IEEE/ SPIE Fellow, IEEE SPS DL), Sparse and Redundant Representations: Theory and Applications
This document discusses machine learning tools and particle swarm optimization for content-based search in large multimedia databases. It begins with an outline and then covers topics like big data sources and characteristics, descriptive and prescriptive analytics using tools like particle swarm optimization, and methods for exploring big data including content-based image retrieval. It also discusses challenges like optimization of non-convex problems and proposes methods like multi-dimensional particle swarm optimization to address issues like premature convergence.
This document discusses compressive spectral image sensing and optimization. It introduces compressive spectral imaging (CASSI) which uses coded apertures to sense a datacube with only N^2 measurements rather than the traditional N x N x L measurements. Coded apertures can be optimized for sensing and reconstruction performance as well as spectral selectivity and image classification. New families of coded apertures include boolean, spectrally selective, super-resolution, and colored apertures.
This document summarizes a talk on influence propagation in large graphs. It discusses theorems and algorithms related to modeling the spread of information, viruses, and diseases over networks. The document begins by motivating the importance of understanding dynamical processes over networks through examples related to epidemiology, viral marketing, cybersecurity, and more. It then outlines threshold results for epidemic models on static graphs that depend on the largest eigenvalue of the graph's adjacency matrix and properties of the propagation model. The talk discusses proofs of these results and also covers extensions to dynamic graphs and competing viruses. Finally, it discusses algorithms for determining who to immunize to control outbreaks.
The document discusses the IEEE Signal Processing Society and the Greek signal processing community. It provides a brief history of signal processing and its influences from other fields. It notes the ubiquity of signals and signal processing. It then summarizes the current state and challenges facing the IEEE Signal Processing Society. It provides details on the local Greek SPS chapter, including its size, activities, and plans for coordinating with the broader Greek signal processing community. These plans include making the Greek SP Jam a regular event and establishing workshops, summer schools, lectures, decentralized events, and awards.
Constantine Kotropoulos, Associate Professor, Aristotle University of Thessaloniki, Department of Informatics, Sparse and Low Rank Representations in Music Signal Analysis
Nicholas Kalouptsidis, Professor, National and Kapodistrian University of Athens, Department of Informatics and Telecommunications, Nonlinear Communications: Achievable Rates, Estimation, and Decoding
Georgios Giannakis, Professor and ADC Chair in Wireless Telecommunications, University of Minnesota, Department of Electrical & Computer Engineering (IEEE/EURASIP Fellow, IEEE SPS DL), Sparsity Control for Robustness and Social Data Analysis
Aristidis Likas, Associate Professor and Christoforos Nikou, Assistant Professor, University of Ioannina, Department of Computer Science , Mixture Models for Image Analysis
Ioannis Pitas, Professor, Aristotle University of Thessaloniki, Department of Informatics (IEEE Fellow), Semantic 3DTV Content Analysis and Description
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help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
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LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
Defying Nyquist in Analog to Digital Conversion
1. Defying Nyquist in Analog to Digital
Conversion
Yonina Eldar
Department of Electrical Engineering
Technion – Israel Institute of Technology
Visiting Professor at Stanford, USA
http://www.ee.technion.ac.il/people/YoninaEldar yonina@ee.technion.ac.il
In collaboration with my students at the Technion
1/20
2. Digital Revolution
“The change from analog mechanical and electronic technology to digital
technology that has taken place since c. 1980 and continues to the present day.”
Cell phone subscribers: 4 billion (67% of world population)
Digital cameras: 77% of American households now own at least one
Internet users: 1.8 billion (26.6% of world population)
PC users: 1 billion (16.8% of world population)
2
3. Sampling: “Analog Girl in a Digital
World…” Judy Gorman 99
Analog world Digital world
Sampling
A2D
Signal processing
Image denoising
Reconstruction Analysis…
Music Very high sampling rates:
Radar D2A
hardware excessive solutions
Image… High DSP rates
(Interpolation)
ADCs, the front end of every digital
application, remain a major bottleneck
3
4. Today’s Paradigm
Analog designers and circuit experts design samplers at Nyquist
rate or higher
DSP/machine learning experts process the data
Typical first step: Throw away (or combine in a “smart” way) much
of the data …
Logic: Exploit structure prevalent in most applications to reduce
DSP processing rates
However, the analog step is one of the costly steps
Can we use the structure to reduce sampling rate + first
DSP rate (data transfer, bus …) as well?
4
5. Key Idea
Exploit structure to improve data processing performance:
Reduce storage/reduce sampling rates
Reduce processing rates
Reduce power consumption
Increase resolution
Improve denoising/deblurring capabilities
Improved classification/source separation
Goal:
Survey the main principles involved in exploiting “sparse” structure
Provide a variety of different applications and benefits
5
6. Talk Outline
Motivation
Classes of structured analog signals
Xampling: Compression + sampling
Sub-Nyquist solutions
Multiband communication: Cognitive radio
Time delay estimation: Ultrasound, radar, multipath
medium identification
Applications to digital processing
6
7. Shannon-Nyquist Sampling
Signal Model Minimal Rate
Analog+Digital
Implementation
ADC DAC
Digital
Signal
Interpolation
Processor
7
8. Structured Analog Models
Multiband communication:
Unknown carriers – non-subspace
Can be viewed as bandlimited (subspace)
But sampling at rate is a waste of resources
For wideband applications Nyquist sampling may be infeasible
Question:
How do we treat structured (non-subspace) models efficiently?
8
9. Cognitive Radio
Cognitive radio mobiles utilize unused spectrum ``holes’’
Spectral map is unknown a-priori, leading to a multiband model
Federal Communications Commission (FCC)
frequency allocation
9
10. Structured Analog Models
Medium identification:
Channel
Similar problem arises in radar, UWB
communications, timing recovery problems … Unknown delays – non-subspace
Digital match filter or super-resolution ideas (MUSIC etc.) (Brukstein,
Kailath, Jouradin, Saarnisaari …)
But requires sampling at the Nyquist rate of
The pulse shape is known – No need to waste sampling resources !
Question (same):
How do we treat structured (non-subspace) models efficiently?
10
11. Ultrasound
High digital processing rates Tx pulse Ultrasonic probe
Large power consumption
(Collaboration with General Electric
Israel)
Rx signal Unknowns
Echoes result from scattering in the tissue
The image is formed by identifying the
scatterers
11
12. Processing Rates
To increase SNR the reflections are viewed by an antenna array
SNR is improved through beamforming by introducing appropriate
time shifts to the received signals
Focusing the received
beam by applying delays
Xdcr
Scan Plane
Requires high sampling rates and large data processing rates
One image trace requires 128 samplers @ 20M, beamforming to 150
points, a total of 6.3x106 sums/frame
12
13. Resolution (1): Radar
Principle:
A known pulse is transmitted
Reflections from targets are received
Target’s ranges and velocities are identified
Challenges:
Targets can lie on an arbitrary grid
Process of digitizing
loss of resolution in range-velocity domain
Wideband radar requires high rate sampling and processing
which also results in long processing time
13
14. Resolution (2): Subwavelength Imaging
(Collaboration with the groups of Segev and Cohen)
Diffraction limit: Even a perfect optical imaging system has a
resolution limit determined by the wavelength λ
The smallest observable detail is larger than ~ λ/2
This results in image smearing
462
464
466
468
470
472
100 nm 474
Sketch of an optical microscope: 476
the physics of EM waves acts 474 476 478 480 482 484 486
Nano-holes Blurred image
as an ideal low-pass filter
as seen in seen in
electronic microscope optical microscope
14
15. Imaging via “Sparse” Modeling
Radar:
Union method
Subwavelength Coherent Diffractive Imaging: Bajwa et al., ‘11
462
464
466
Recovery of
468 sub-wavelength images
470
from highly truncated
472
474
Fourier power spectrum
476
474 476 478 480 482 484 486
150 nm et al., Nature Photonics, ‘12
Szameit
15
16. Proposed Framework
Instead of a single subspace modeling use union of subspaces
framework
Adopt a new design methodology – Xampling
Compression+Sampling = Xampling
X prefix for compression, e.g. DivX
Results in simple hardware and low computational cost on
the DSP
Union + Xampling = Practical Low Rate Sampling
16
17. Talk Outline
Motivation
Classes of structured analog signals
Xampling: Compression + sampling
Sub-Nyquist solutions
Multiband communication: Cognitive radio
Time delay estimation: Ultrasound, radar, multipath
medium identification
Applications to digital processing
17
18. Union of Subspaces
(Lu and Do 08, Eldar and Mishali 09)
Model:
Examples:
18
19. Union of Subspaces
(Lu and Do 08, Eldar and Mishali 09)
Model:
Standard approach: Look at sum of all subspaces
Signal bandlimited to
High rate
19
20. Union of Subspaces
(Lu and Do 08, Eldar and Mishali 09)
Model:
Examples:
20
21. Union of Subspaces
(Lu and Do 08, Eldar and Mishali 09)
Model:
Allows to keep low dimension in the problem model
Low dimension translates to low sampling rate
21
22. Talk Outline
Motivation
Classes of structured analog signals
Xampling: Compression + sampling
Sub-Nyquist solutions
Multiband communication: Cognitive radio
Time delay estimation: Ultrasound, radar, multipath
medium identification
Applications to digital processing
22
23. Difficulty
Naïve attempt: direct sampling at low rate
Most samples do not contain information!!
Most bands do not have energy – which band should be sampled?
~
~
~
23
24. Intuitive Solution: Pre-Processing
Smear pulse before sampling
Each samples contains energy
Resolve ambiguity in the digital domain
Alias all energy to baseband
Can sample at low rate
Resolve ambiguity in the digital domain
~
~
~
24
25. Xampling: Main Idea
Create several streams of data
Each stream is sampled at a low rate
(overall rate much smaller than the Nyquist rate)
Each stream contains a combination from different subspaces
Hardware design ideas
Identify subspaces involved
Recover using standard sampling results
DSP algorithms
25
26. Subspace Identification
For linear methods:
Subspace techniques developed in the context of array
processing (such as MUSIC, ESPRIT etc.)
Compressed sensing: only for subspace identification
For nonlinear sampling:
Specialized iterative algorithms: quadratic compressed
sensing and more generally nonlinear compressed sensing
26
29. Compressed Sensing and Hardware
Explosion of work on compressed sensing in many digital
applications
Many papers describing models for CS of analog signals
Have these systems made it into hardware?
CS is a digital theory – treats vectors not analog inputs
Standard CS Analog CS
Input vector x analog signal x(t)
Sparsity few nonzero values ?
Measurement random matrix real hardware
Recovery convex optimization need to recover analog input
greedy methods
We use CS only after sampling and only to detect the subspace
Enables efficient hardware and low processing rates
29
30. Optimal Xampling Hardware
Sampling Reconstruction
(det. by )
White
Gaussian
noise
We derive two lower bounds on the performance of UoS estimation:
Fundamental limit – regardless of sampling technique or rate
Lower bound for a given sampling rate
Allows to determine optimal sampling method
Can compare practical algorithms to bound
Ben-Haim, Michaeli, and Eldar (2010), “Performance Bounds and Design Criteria
for Estimating Finite Rate of Innovation Signals,” to appear in IEEE Trans. Inf. Theory.
Sampling with Sinusoids is Optimal
30
31. Xampling Hardware
- periodic functions
sums of exponentials
The filter H(f) allows for additional freedom in shaping the tones
The channels can be collapsed to a single channel
31
32. Talk Outline
Motivation
Classes of structured analog signals
Xampling: Compression + sampling
Sub-Nyquist solutions
Multiband communication
Time delay estimation: Ultrasound, radar, multipath
medium identification
Applications to digital processing
32
33. Signal Model
(Mishali and Eldar, 2007-2009)
~
~
~
1. Each band has an uncountable 2. Band locations lie on the continuum
number of non-zero elements
3. Band locations are unknown in advance
no more than N bands, max width B, bandlimited to
33
34. Rate Requirement
Theorem (Single multiband subspace)
(Landau 1967)
Average sampling rate
Theorem (Union of multiband subspaces)
(Mishali and Eldar 2007)
1. The minimal rate is doubled.
2. For , the rate requirement is samples/sec (on average).
34
36. Recovery From Xamples
~
~
~
Spectrum sparsity: Most of the are identically zero
For each n we have a small size CS problem
Problem: CS algorithms for each n many computations
Solution: Use the ``CTF’’ block which exploits the joint sparsity and
reduces the problem to a single finite CS problem
36
37. A 2.4 GHz Prototype
(Mishali, Eldar, Dounaevsky, and Shoshan, 2010)
Rate proportional to the actual band occupancy
All DSP done at low rate as well
2.3 GHz Nyquist-rate, 120 MHz occupancy
280 MHz sampling rate
Wideband receiver mode:
49 dB dynamic range, SNDR > 30 dB over all input range
ADC mode:
1.2 volt peak-to-peak full-scale, 42 dB SNDR = 6.7 ENOB
37
38. Sub-Nyquist Demonstration
Carrier frequencies are chosen to create overlayed aliasing at baeband
+ +
Overlayed sub-Nyquist
FM @ 631.2 MHz AM @ 807.8 MHz Sine @ 981.9 MHz MWC prototype aliasing around 6.171 MHz
10 kHz 100 kHz
1.5 MHz
Reconstruction
(CTF)
FM @ 631.2 MHz AM @ 807.8 MHz
Mishali et al., 10
38
39. Online Demonstrations
GUI package of the MWC
Video recording of sub-Nyquist sampling + carrier recovery in lab
SiPS 2010
2010 IEEE Workshop on
Signal Processing Systems
39
40. Talk Outline
Brief overview of standard sampling
Classes of structured analog signals
Xampling: Compression + sampling
Sub-Nyquist solutions
Multiband communication
Time delay estimation:
Ultrasound, radar, multipath medium identification
Applications to digital processing
40
41. Streams of Pulses
(Gedalyahu, Tur, Eldar 10, Tur, Freidman, Eldar 10)
is replaced by an integrator
Can equivalently be implemented as a single channel with
Application to radar, ultrasound and general localization problems such as GPS
41
42. Unknown Pulses
(Matusiak and Eldar, 11)
Output corresponds to aliased version of Gabor coefficients
Recovery by solving 2-step CS problem
Row-sparse Gabor Coeff.
42
43. Noise Robustness
MSE of the delays estimation, versus integrators approach (Kusuma & Goyal )
L=2 pulses, 5 samples L=10 pulses, 21 samples
40 40
20 20
0 0
-20 -20
MSE [dB]
MSE [dB]
-40 -40
-60 -60
-80 -80
proposed method proposed method
-100 integrators -100 integrators
0 10 20 30 40 50 60 70 80 90 0 10 20 30 40 50 60 70 80 90
SNR [dB] SNR [dB]
The proposed scheme is stable even for high rates of innovation!
43
44. Application:
Multipath Medium Identification
(Gedalyahu and Eldar 09-10)
LTV channel
propagation paths
pulses per period
Medium identification (collaboration with National Instruments):
Recovery of the time delays
Recovery of time-variant gain coefficients
The proposed method can recover the channel parameters from
sub-Nyquist samples
44
45. Application: Radar
Each target is defined by: (Bajwa, Gedalyahu and Eldar, 10)
Range – delay
Velocity – doppler
Targets can be identified with infinite
resolution as long as the time-bandwidth
product satisfies
Previous results required infinite time-
bandwidth product
45
46. Xampling in Ultrasound Imaging
Wagner, Eldar, and Friedman, ’11
A scheme which enables reconstruction of a two dimensional
image, from samples obtained at a rate 10-15 times below Nyquist
The resulting image depicts strong perturbations in the tissue
Obtained by beamforming in the compressed domain
Standard Imaging Xampled beamforming
1662 real-valued samples, per sensor 200 real-valued samples, per sensor per
per image line image line (assume L=25 reflectors per line)
46
47. Nonlinear Sampling
Michaeli & Eldar, ’12
Results can be extended to include many classes of nonlinear
sampling
Example: Nonlinear Sampling
In particular we have extended these ideas to phase retrieval
problems where we recover signals from samples of the Fourier
transform magnitude (Candes et. al., Szameit et. al., Shechtman et. al.)
Many applications in optics: recovery from partially coherent light,
crystallography, subwavelength imaging and more
47
48. Structure in Digital Problems
Union of subspaces structure can be exploited in many digital models
Subspace models lead to block sparse recovery
Block sparsity: algorithms and recovery guarantees in noisy environments
(Eldar and Mishali 09, Eldar et. al. 10, Ben-Haim and Eldar 10)
Hierarchical models with structure on the subspace level and within the
subspaces (Sprechmann, Ramirez, Sapiro and Eldar, 10)
Noisy merged Missing pixels Separated
48
50. Subspace Learning
Prior work has focused primarily on learning a single subspace
(Vidal et. al., Ma et. al., Elhamifar …)
We developed methods for multiple subspace learning from training
data (Rosenblum, Zelnik-Manor and Eldar, 10)
Subspace learning from reduced-dimensional measured data: Blind
compressed sensing (Gleichman and Eldar 10)
Current work: Extending these ideas to more practical scenarios (Carin, Silva,
Chen, Sapiro)
50
52. Conclusions
Compressed sampling and processing of many signals
Wideband sub-Nyquist samplers in hardware
Union of subspaces: broad and flexible model
Practical and efficient hardware
Many applications and many research opportunities: extensions to
other analog and digital problems, robustness, hardware …
Exploiting structure can lead to a new sampling
paradigm which combines analog + digital
More details in:
M. Duarte and Y. C. Eldar, “Structured Compressed Sensing: From Theory to Applications,” Review for TSP.
M. Mishali and Y. C. Eldar, "Xampling: Compressed Sensing for Analog Signals", book chapter available at
http://webee.technion.ac.il/Sites/People/YoninaEldar/books.html
52
53. Xampling Website
webee.technion.ac.il/people/YoninaEldar/xampling_top.html
Y. C. Eldar and G. Kutyniok, "Compressed Sensing: Theory and Applications",
Cambridge University Press, to appear in 2012
53