The document provides an overview of orthogonal frequency-division multiplexing (OFDM) and multiple-input multiple-output (MIMO) wireless communication techniques. It discusses the motivation for OFDM including dealing with delay spread and increasing data rates. Key concepts of OFDM like multicarrier transmission, cyclic prefix, and bit error rate calculation are summarized. An example of an OFDM system used in WiMAX is provided. MIMO wireless systems employing multiple antennas for diversity gain and spatial multiplexing are also introduced.
Ramin Anushiravani's document outlines techniques for sound source localization using microphone arrays. It discusses beamforming methods like delay-and-sum and MVDR beamforming, as well as subspace-based algorithms like MUSIC. It also covers topics like uniform linear arrays, beampatterns, and spatial aliasing. The document presents results from experiments localizing 1-2 sound sources using arrays with 2-4 microphones.
Voice Activity Detection using Single Frequency FilteringTejus Adiga M
1. Voice Activity Detection (VAD) aims to locate speech segments in an input signal corrupted by noise by classifying frames as speech or noise.
2. Several time domain and frequency domain algorithms are discussed for VAD, including short-term energy, zero crossing rate, frequency subband distance measure, and long-term spectral flatness measure.
3. Single frequency filtering is also described, which analyzes envelopes at discrete frequencies to classify frames based on a learned noise floor.
The program demonstrates linear and circular convolution of sequences using MATLAB. For linear convolution, the conv function is used to convolve two input sequences and plot the results. For circular convolution, the FFT of each sequence is taken, multiplied together and inverse FFT applied to obtain the output, which is also plotted. The program thus allows generation and visualization of linear and circular convolution.
1. The document discusses multi-carrier transmission over mobile radio channels. It introduces OFDM and describes how multipath reception affects different modulation techniques.
2. It then discusses receivers for OFDM and MC-CDMA, including synchronous MC-CDMA receivers that use FFT processing followed by weighting and code despreading.
3. The effects of Doppler spread on OFDM and MC-CDMA are analyzed, including intercarrier interference and its impact on BER performance in mobile channels. The channel is modeled using a Taylor expansion of the time-varying amplitude.
This document discusses multi-carrier transmission over mobile radio channels. It introduces OFDM and MC-CDMA techniques for combating multipath interference in mobile channels. It describes various receiver designs for OFDM and MC-CDMA, including matrix inversion and decision feedback equalization approaches to estimate channel amplitudes and derivatives in order to reduce intercarrier interference caused by Doppler spread. Simulation results show performance improvements of these techniques over conventional OFDM.
1) The document discusses using an autocorrelation function (ACF) filter on burst image sequences to reduce noise in CMOS image sensors and achieve high quality imaging.
2) It explains that the ACF calculates correlation values based on pixel values sampled over time to distinguish random noise from true signals. Noise pixels will have lower ACF values while true signals have higher values near 1.
3) The algorithm judges each pixel, applying a leveling filter only to pixels below thresholds for value and ACF. This reduces random noise without impacting bright pixels and resolution. Results show noise reduction while maintaining detail.
Multi-Carrier Transmission over Mobile Radio Channels.pptStefan Oprea
This document summarizes a presentation on multi-carrier transmission over mobile radio channels. It introduces OFDM and discusses how multipath reception affects different modulation techniques. It then focuses on MC-CDMA, a type of multi-carrier CDMA that applies CDMA spreading after an IFFT. The document analyzes the performance of MC-CDMA in mobile channels affected by Doppler spread and intercarrier interference. It shows through simulations that MC-CDMA can outperform uncoded OFDM in such channels. In conclusion, the document evaluates capacity and discusses how to model mobile multipath channels and their impact on OFDM and MC-CDMA receivers.
The document provides an overview of orthogonal frequency-division multiplexing (OFDM) and multiple-input multiple-output (MIMO) wireless communication techniques. It discusses the motivation for OFDM including dealing with delay spread and increasing data rates. Key concepts of OFDM like multicarrier transmission, cyclic prefix, and bit error rate calculation are summarized. An example of an OFDM system used in WiMAX is provided. MIMO wireless systems employing multiple antennas for diversity gain and spatial multiplexing are also introduced.
Ramin Anushiravani's document outlines techniques for sound source localization using microphone arrays. It discusses beamforming methods like delay-and-sum and MVDR beamforming, as well as subspace-based algorithms like MUSIC. It also covers topics like uniform linear arrays, beampatterns, and spatial aliasing. The document presents results from experiments localizing 1-2 sound sources using arrays with 2-4 microphones.
Voice Activity Detection using Single Frequency FilteringTejus Adiga M
1. Voice Activity Detection (VAD) aims to locate speech segments in an input signal corrupted by noise by classifying frames as speech or noise.
2. Several time domain and frequency domain algorithms are discussed for VAD, including short-term energy, zero crossing rate, frequency subband distance measure, and long-term spectral flatness measure.
3. Single frequency filtering is also described, which analyzes envelopes at discrete frequencies to classify frames based on a learned noise floor.
The program demonstrates linear and circular convolution of sequences using MATLAB. For linear convolution, the conv function is used to convolve two input sequences and plot the results. For circular convolution, the FFT of each sequence is taken, multiplied together and inverse FFT applied to obtain the output, which is also plotted. The program thus allows generation and visualization of linear and circular convolution.
1. The document discusses multi-carrier transmission over mobile radio channels. It introduces OFDM and describes how multipath reception affects different modulation techniques.
2. It then discusses receivers for OFDM and MC-CDMA, including synchronous MC-CDMA receivers that use FFT processing followed by weighting and code despreading.
3. The effects of Doppler spread on OFDM and MC-CDMA are analyzed, including intercarrier interference and its impact on BER performance in mobile channels. The channel is modeled using a Taylor expansion of the time-varying amplitude.
This document discusses multi-carrier transmission over mobile radio channels. It introduces OFDM and MC-CDMA techniques for combating multipath interference in mobile channels. It describes various receiver designs for OFDM and MC-CDMA, including matrix inversion and decision feedback equalization approaches to estimate channel amplitudes and derivatives in order to reduce intercarrier interference caused by Doppler spread. Simulation results show performance improvements of these techniques over conventional OFDM.
1) The document discusses using an autocorrelation function (ACF) filter on burst image sequences to reduce noise in CMOS image sensors and achieve high quality imaging.
2) It explains that the ACF calculates correlation values based on pixel values sampled over time to distinguish random noise from true signals. Noise pixels will have lower ACF values while true signals have higher values near 1.
3) The algorithm judges each pixel, applying a leveling filter only to pixels below thresholds for value and ACF. This reduces random noise without impacting bright pixels and resolution. Results show noise reduction while maintaining detail.
Multi-Carrier Transmission over Mobile Radio Channels.pptStefan Oprea
This document summarizes a presentation on multi-carrier transmission over mobile radio channels. It introduces OFDM and discusses how multipath reception affects different modulation techniques. It then focuses on MC-CDMA, a type of multi-carrier CDMA that applies CDMA spreading after an IFFT. The document analyzes the performance of MC-CDMA in mobile channels affected by Doppler spread and intercarrier interference. It shows through simulations that MC-CDMA can outperform uncoded OFDM in such channels. In conclusion, the document evaluates capacity and discusses how to model mobile multipath channels and their impact on OFDM and MC-CDMA receivers.
Sander Dieleman, Research Scientist at DeepMind - Generating Music in the Ra...Codiax
This document summarizes Sander Dieleman's presentation on generating music in the raw audio domain using WaveNet models. It discusses why modeling music at the raw audio level is important, introduces the WaveNet model for modeling raw audio, and describes how WaveNets can be used to generate musical audio. It also covers techniques for improving WaveNets' ability to model long-range correlations in audio, such as autoregressive discrete autoencoders.
The document discusses various topics related to pulse modulation systems including sampling, Pulse Code Modulation (PCM), and quantization noise. Some key points:
1. A signal can be recovered from its samples by passing it through an ideal low-pass filter with the appropriate bandwidth to remove aliases introduced by sampling.
2. In PCM, the maximum quantization error occurs when the analog voltage being converted is at the midpoint between two quantization levels, and equals half the voltage interval size.
3. Increasing the number of bits per sample in a PCM system increases the signal-to-quantization noise ratio by 6 dB, as each additional bit provides an increase of 6 dB.
This presentation covers noise performance of Continuous wave modulation systems; It explains modelling of white noise , noise figure of DSB-SC, SSB, AM, FM system
The document discusses pulse code modulation (PCM) for encoding analog waveforms into digital signals. It covers:
1. PCM involves sampling, quantizing, and encoding analog signals. Sampling makes the signal discrete in time. Quantizing makes it discrete in amplitude by rounding to discrete levels. Encoding maps quantized values to binary code words.
2. Quantization introduces distortion but sampling noise can be eliminated if the Nyquist criterion is met. Uniform quantizers are optimal for uniformly distributed inputs.
3. A practical PCM system was designed for telephone systems using 8-bit samples at 8 kHz to encode voice signals between 300-3400 Hz, producing a 64 kbps digital signal. The bandwidth
Detection of Power Line Disturbances using DSP TechniquesKashishVerma18
This document summarizes Kashish Verma's presentation on detecting power line disturbances using digital signal processing techniques. It discusses using Simulink models to simulate normal and disturbed power systems. Various DSP techniques for frequency estimation like Prony analysis, FFT, SVD, MUSIC, and ESPIRIT are described along with their advantages and drawbacks. Detection of faults during power swings using methods like Prony analysis, wavelet transform, and ANFIS is also summarized. Overall, the document provides an overview of modeling power systems and applying DSP for fault detection and frequency estimation.
The document discusses active noise cancellation and noise reduction techniques. It describes how active noise cancellation works by generating a sound wave with equal amplitude but opposite phase to the original noise, cancelling it out. Adaptive filters are used, with algorithms like LMS and RLS, to analyze input sounds and adjust filter coefficients to minimize noise. Applications include headphones, vehicles, aircraft, and noise-cancelling devices that can reduce ambient sounds.
This document provides an overview of signals and systems. It begins with an introduction to signals, including definitions of key signal properties such as periodicity, causality, boundedness. It also distinguishes between continuous-time and discrete-time signals. The document then covers fundamental signal types including sinusoidal, exponential, unit step, and impulse signals. It concludes with discussions of signal processing concepts like the Fourier transform and basics of communication systems.
The document describes experiments conducted in MATLAB to visualize and understand various continuous-time and discrete-time signals. In experiment 1, common continuous signals like unit step, ramp, impulse etc. are plotted. Experiment 2 involves plotting corresponding discrete-time signals. The document provides MATLAB code examples to generate and plot these standard signals.
CHƯƠNG 2 KỸ THUẬT TRUYỀN DẪN SỐ - THONG TIN SỐlykhnh386525
Digitization involves representing an analog signal in digital form through sampling and quantization.
Sampling is the process of capturing the signal's amplitude at regular time intervals. If the sampling frequency is greater than twice the highest frequency present in the signal (as per the Nyquist sampling theorem), the original signal can be reconstructed perfectly from the samples. Quantization maps the continuous range of sampled amplitudes to a finite set of values, introducing quantization error. Both sampling and quantization are required to convert an analog signal to digital.
Vidyalankar final-essentials of communication systemsanilkurhekar
This document provides an overview of analog and digital communication systems. It discusses the basics of analog signals, frequency spectrum, and modulation. It then covers digital signals, terms, and performance metrics like data rate and bit error probability. Key concepts covered include Shannon capacity, signal energy and power, communication system blocks, filtering, and modulation. It also introduces concepts from probability theory and random processes used in analysis of communication systems like mean, autocorrelation, power spectral density, Gaussian processes, and noise. Examples of modulation techniques and noise sources in communication systems are briefly discussed.
The document discusses the challenges of ground-based astronomical array imaging at far-infrared wavelengths. It covers topics such as data reduction techniques like direct mapping and iterative map-making methods. Scanning strategies that provide noise resistance, large-scale sensitivity, and coverage are explored through simulations. Common strategies like on-the-fly scanning, Lissajous patterns, billiard scans, and spirals are analyzed and compared. Examples of real observations using these techniques are also presented. The document emphasizes that careful consideration of both data reduction methods and scanning strategies is needed to produce high-quality images from ground-based submillimeter arrays.
Tutorial on neural vocoders at the 2021 Speech Processing Courses in Crete, "Inclusive Neural Speech Synthesis."
Presenters: Xin Wang and Junichi Yamagishi, National Institute of Informatics, Japan
Sander Dieleman - Generating music in the raw audio domain - Creative AI meetupLuba Elliott
This talk by Sander Dieleman from DeepMind on "Generating music in the raw audio domain" was presented on 10th September 2018 at IDEA London as part of the Creative AI meetup.
Signal Processing Algorithms for MIMO Radarsansam77
The document outlines Chun-Yang Chen's candidacy presentation on signal processing algorithms for MIMO radar. It begins with a review of MIMO radar and space-time adaptive processing (STAP). It then proposes a new MIMO-STAP method, including formulations, representations of clutter signals, and simulations. The conclusion discusses future work. Key points covered include MIMO radar transmitting orthogonal waveforms, using antenna arrays for beamforming to control directionality digitally, and adapting beams to interference.
This document discusses front-end audio processing techniques used in communication and recording devices. It provides an overview of classical front-end architectures used in phones from the 1990s to 2010, including filters, equalizers, encoders/decoders, volume control, acoustic echo cancellation, noise suppression, and leveling. It also discusses issues like dynamic range, quantization noise, distortion, and the tradeoffs between noise suppression and voice quality. The document reviews single-channel noise suppression techniques and metrics like convergence rate and PESQ/MOS-LQO. Finally, it introduces multi-microphone solutions like linear beamforming and differential beamforming and their benefits and limitations regarding critical distance and noise.
Communication Engineering - Chapter 6 - Noisemkazree
This document discusses various types of noise that can interfere with communication signals. It defines noise and categorizes it as either correlated noise, which depends on the presence of a signal, or uncorrelated noise, which is always present. Examples of uncorrelated noise sources include atmospheric noise from lightning, extraterrestrial noise from the sun and stars, industrial noise from machinery, thermal noise from component movement, and shot noise from random carrier arrival. The effects of noise on signals and ways to measure noise are also summarized.
This document discusses different types of antennas used in wireless communication systems. It begins with an introduction to antennas and their basic parameters. The document then covers the history of antenna development. Several common antenna types are described, including Yagi-Uda antennas, log-periodic antennas, horn antennas, loop antennas, and parabolic antennas. Each antenna type is defined along with its advantages and applications. The document concludes that antennas play an important role in converting signals for transmission and reception in modern wireless technologies.
The document discusses different types of antennas used in wireless communication. It describes antennas such as dipole antennas, horn antennas, parabolic dish antennas, and antenna arrays. Dipole antennas are simple and widely used. They consist of two conductive elements that transmit and receive electromagnetic waves. Horn antennas guide radio waves into a beam but have limited directivity. Parabolic dish antennas have high gain and directivity due to their distinctive parabolic shape. Antenna arrays combine the radiation patterns of individual antenna elements to provide benefits such as high gain and directivity.
Sander Dieleman, Research Scientist at DeepMind - Generating Music in the Ra...Codiax
This document summarizes Sander Dieleman's presentation on generating music in the raw audio domain using WaveNet models. It discusses why modeling music at the raw audio level is important, introduces the WaveNet model for modeling raw audio, and describes how WaveNets can be used to generate musical audio. It also covers techniques for improving WaveNets' ability to model long-range correlations in audio, such as autoregressive discrete autoencoders.
The document discusses various topics related to pulse modulation systems including sampling, Pulse Code Modulation (PCM), and quantization noise. Some key points:
1. A signal can be recovered from its samples by passing it through an ideal low-pass filter with the appropriate bandwidth to remove aliases introduced by sampling.
2. In PCM, the maximum quantization error occurs when the analog voltage being converted is at the midpoint between two quantization levels, and equals half the voltage interval size.
3. Increasing the number of bits per sample in a PCM system increases the signal-to-quantization noise ratio by 6 dB, as each additional bit provides an increase of 6 dB.
This presentation covers noise performance of Continuous wave modulation systems; It explains modelling of white noise , noise figure of DSB-SC, SSB, AM, FM system
The document discusses pulse code modulation (PCM) for encoding analog waveforms into digital signals. It covers:
1. PCM involves sampling, quantizing, and encoding analog signals. Sampling makes the signal discrete in time. Quantizing makes it discrete in amplitude by rounding to discrete levels. Encoding maps quantized values to binary code words.
2. Quantization introduces distortion but sampling noise can be eliminated if the Nyquist criterion is met. Uniform quantizers are optimal for uniformly distributed inputs.
3. A practical PCM system was designed for telephone systems using 8-bit samples at 8 kHz to encode voice signals between 300-3400 Hz, producing a 64 kbps digital signal. The bandwidth
Detection of Power Line Disturbances using DSP TechniquesKashishVerma18
This document summarizes Kashish Verma's presentation on detecting power line disturbances using digital signal processing techniques. It discusses using Simulink models to simulate normal and disturbed power systems. Various DSP techniques for frequency estimation like Prony analysis, FFT, SVD, MUSIC, and ESPIRIT are described along with their advantages and drawbacks. Detection of faults during power swings using methods like Prony analysis, wavelet transform, and ANFIS is also summarized. Overall, the document provides an overview of modeling power systems and applying DSP for fault detection and frequency estimation.
The document discusses active noise cancellation and noise reduction techniques. It describes how active noise cancellation works by generating a sound wave with equal amplitude but opposite phase to the original noise, cancelling it out. Adaptive filters are used, with algorithms like LMS and RLS, to analyze input sounds and adjust filter coefficients to minimize noise. Applications include headphones, vehicles, aircraft, and noise-cancelling devices that can reduce ambient sounds.
This document provides an overview of signals and systems. It begins with an introduction to signals, including definitions of key signal properties such as periodicity, causality, boundedness. It also distinguishes between continuous-time and discrete-time signals. The document then covers fundamental signal types including sinusoidal, exponential, unit step, and impulse signals. It concludes with discussions of signal processing concepts like the Fourier transform and basics of communication systems.
The document describes experiments conducted in MATLAB to visualize and understand various continuous-time and discrete-time signals. In experiment 1, common continuous signals like unit step, ramp, impulse etc. are plotted. Experiment 2 involves plotting corresponding discrete-time signals. The document provides MATLAB code examples to generate and plot these standard signals.
CHƯƠNG 2 KỸ THUẬT TRUYỀN DẪN SỐ - THONG TIN SỐlykhnh386525
Digitization involves representing an analog signal in digital form through sampling and quantization.
Sampling is the process of capturing the signal's amplitude at regular time intervals. If the sampling frequency is greater than twice the highest frequency present in the signal (as per the Nyquist sampling theorem), the original signal can be reconstructed perfectly from the samples. Quantization maps the continuous range of sampled amplitudes to a finite set of values, introducing quantization error. Both sampling and quantization are required to convert an analog signal to digital.
Vidyalankar final-essentials of communication systemsanilkurhekar
This document provides an overview of analog and digital communication systems. It discusses the basics of analog signals, frequency spectrum, and modulation. It then covers digital signals, terms, and performance metrics like data rate and bit error probability. Key concepts covered include Shannon capacity, signal energy and power, communication system blocks, filtering, and modulation. It also introduces concepts from probability theory and random processes used in analysis of communication systems like mean, autocorrelation, power spectral density, Gaussian processes, and noise. Examples of modulation techniques and noise sources in communication systems are briefly discussed.
The document discusses the challenges of ground-based astronomical array imaging at far-infrared wavelengths. It covers topics such as data reduction techniques like direct mapping and iterative map-making methods. Scanning strategies that provide noise resistance, large-scale sensitivity, and coverage are explored through simulations. Common strategies like on-the-fly scanning, Lissajous patterns, billiard scans, and spirals are analyzed and compared. Examples of real observations using these techniques are also presented. The document emphasizes that careful consideration of both data reduction methods and scanning strategies is needed to produce high-quality images from ground-based submillimeter arrays.
Tutorial on neural vocoders at the 2021 Speech Processing Courses in Crete, "Inclusive Neural Speech Synthesis."
Presenters: Xin Wang and Junichi Yamagishi, National Institute of Informatics, Japan
Sander Dieleman - Generating music in the raw audio domain - Creative AI meetupLuba Elliott
This talk by Sander Dieleman from DeepMind on "Generating music in the raw audio domain" was presented on 10th September 2018 at IDEA London as part of the Creative AI meetup.
Signal Processing Algorithms for MIMO Radarsansam77
The document outlines Chun-Yang Chen's candidacy presentation on signal processing algorithms for MIMO radar. It begins with a review of MIMO radar and space-time adaptive processing (STAP). It then proposes a new MIMO-STAP method, including formulations, representations of clutter signals, and simulations. The conclusion discusses future work. Key points covered include MIMO radar transmitting orthogonal waveforms, using antenna arrays for beamforming to control directionality digitally, and adapting beams to interference.
This document discusses front-end audio processing techniques used in communication and recording devices. It provides an overview of classical front-end architectures used in phones from the 1990s to 2010, including filters, equalizers, encoders/decoders, volume control, acoustic echo cancellation, noise suppression, and leveling. It also discusses issues like dynamic range, quantization noise, distortion, and the tradeoffs between noise suppression and voice quality. The document reviews single-channel noise suppression techniques and metrics like convergence rate and PESQ/MOS-LQO. Finally, it introduces multi-microphone solutions like linear beamforming and differential beamforming and their benefits and limitations regarding critical distance and noise.
Communication Engineering - Chapter 6 - Noisemkazree
This document discusses various types of noise that can interfere with communication signals. It defines noise and categorizes it as either correlated noise, which depends on the presence of a signal, or uncorrelated noise, which is always present. Examples of uncorrelated noise sources include atmospheric noise from lightning, extraterrestrial noise from the sun and stars, industrial noise from machinery, thermal noise from component movement, and shot noise from random carrier arrival. The effects of noise on signals and ways to measure noise are also summarized.
This document discusses different types of antennas used in wireless communication systems. It begins with an introduction to antennas and their basic parameters. The document then covers the history of antenna development. Several common antenna types are described, including Yagi-Uda antennas, log-periodic antennas, horn antennas, loop antennas, and parabolic antennas. Each antenna type is defined along with its advantages and applications. The document concludes that antennas play an important role in converting signals for transmission and reception in modern wireless technologies.
The document discusses different types of antennas used in wireless communication. It describes antennas such as dipole antennas, horn antennas, parabolic dish antennas, and antenna arrays. Dipole antennas are simple and widely used. They consist of two conductive elements that transmit and receive electromagnetic waves. Horn antennas guide radio waves into a beam but have limited directivity. Parabolic dish antennas have high gain and directivity due to their distinctive parabolic shape. Antenna arrays combine the radiation patterns of individual antenna elements to provide benefits such as high gain and directivity.
This document provides an overview of antennas, including:
- Antennas are devices that radiate or receive radio frequency (RF) signals. Common antennas range from simple single wires to complex dishes.
- Antenna behavior is the same whether transmitting or receiving due to the reciprocity principle. However, performance depends on how it's used and the connected electronics.
- Antenna gain is a measure of power radiated in a given direction compared to an isotropic antenna. Higher gain antennas focus power into narrower beams.
- Common antenna types include half-wave dipoles and quarter-wave Marconi antennas. Coaxial cables are often used to connect asymmetric antennas like dipoles to electronics.
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The document discusses radar clutter and methods for eliminating it. Clutter refers to radar targets that are not of interest to the user, usually caused by static objects near the radar. Doppler filtering is used to eliminate clutter by taking advantage of the fact that desired targets are moving relative to the radar. Pulse modulation and coherent demodulation allow extracting the Doppler frequency shift from returned signals. Various cancellation techniques can then be applied, including delay line cancellers and transversal filters, to attenuate clutter signals based on their Doppler frequency.
This document contains slides from a course on radar systems presented by MIT Lincoln Laboratory. It discusses various techniques for clutter rejection in radar, including Moving Target Indicator (MTI) processing and Pulse Doppler processing. MTI uses short waveforms to separate moving targets from clutter without estimating target velocity, while Pulse Doppler processing coherently integrates pulses over longer time intervals to resolve targets by velocity and estimate Doppler. Range and Doppler ambiguities are also addressed.
This document discusses MTI (Moving Target Indication) and pulse Doppler radars. It begins by explaining how clutter like land, sea, and weather can interfere with radar detection of targets. It then describes the Doppler effect which causes a shift in frequency when the radar or target is in motion, allowing CW radars to detect moving targets. MTI radars use a technique called pulse cancellation to remove stationary clutter and detect moving targets. Pulse Doppler radars also use Doppler shift but have a high pulse repetition frequency which avoids ambiguities. The document discusses limitations of CW and MTI radars and techniques to overcome them like using multiple frequencies or pulse repetition frequencies. It includes diagrams of radar systems and equations for Doppler shift.
Radar is an acronym for Radio Detection And Ranging. It uses electromagnetic waves to detect the position and movement of distant objects. Radar was originally developed for military use during World War II to locate enemy ships and planes. Today radar has many applications including weather monitoring, air traffic control, and police speed detection. It works by transmitting radio pulses and measuring their reflection off targets to determine the target's range, angle, and velocity.
The document discusses radar clutter and techniques for eliminating it. It describes how clutter is unwanted radar targets that are not of interest. Doppler shift from moving targets can be used to distinguish targets from clutter. Pulse modulation and coherent demodulation preserves the phase of returning signals. Transversal filters with binomial weighting and alternating signs can sharply attenuate clutter while maximizing the clutter improvement factor, but may also cut off some legitimate target signals as the number of taps increases.
The document discusses MTI (Moving Target Indication) and pulse Doppler radars. It explains that MTI radars use techniques like delay line cancellation to eliminate echoes from stationary clutter and detect moving targets. Pulse Doppler radars employ the Doppler shift caused by target motion to detect targets. Key differences are noted - MTI radars have no range ambiguities but Doppler ambiguities, while pulse Doppler radars have the opposite problem. Blind speeds, limitations of CW radar, and techniques to overcome issues like flicker noise and lack of isolation are also covered. Applications of CW radar like speed measurement are mentioned.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
1. Microphone array beamforming
Pouyan Ebrahimbabaie
Laboratory for Signal and Image Exploitation (INTELSIG)
Dept. of Electrical Engineering and Computer Science
University of Liège
Liège, Belgium
Introduction to audio and video techniques (ELEN0002-2)
November 2020
MATLAB tutorial series (Part 1)
10. 𝑥
Sound card
16 x .wav
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Compare two signals (with and without beamforming)
Output signal (N x 1)
11. 𝑥
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16 x .wav
16 x mic.
Read 16 x .wav’s into a single matrix sigArray (N x 16)
sigArray (N x 16)
Multiply each column by its corresponding
correction coefficient
Filter sigArray with a
bandpass filter (300 Hz – 3400 Hz)
Corrected sigArray
Play an arbitrary column
Filtered sigArray
Apply time-delay beamforming on sigArray
Play the output signal
Compare two signals (with and without beamforming)
Output signal (N x 1)
12. 𝑥
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16 x .wav
16 x mic.
Read 16 x .wav’s into a single matrix sigArray (N x 16)
sigArray (N x 16)
Multiply each column by its corresponding
correction coefficient
Filter sigArray with a
bandpass filter (300 Hz – 3400 Hz)
Corrected sigArray
Play an arbitrary column
Filtered sigArray
Apply time-delay beamforming on sigArray
Play the output signal
Compare two signals (with and without beamforming)
Output signal (N x 1)
13. 𝑥
Sound card
16 x .wav
16 x mic.
Read 16 x .wav’s into a single matrix sigArray (N x 16)
sigArray (N x 16)
Multiply each column by its corresponding
correction coefficient
Filter sigArray with a
bandpass filter (300 Hz – 3400 Hz)
Corrected sigArray
Play an arbitrary column
Filtered sigArray
Apply time-delay beamforming on sigArray
Play the output signal
Compare two signals (with and without beamforming)
Output signal (N x 1)
14. 𝑥
Sound card
16 x .wav
16 x mic.
Read 16 x .wav’s into a single matrix sigArray (N x 16)
sigArray (N x 16)
Multiply each column by its corresponding
correction coefficient
Filter sigArray with a
bandpass filter (300 Hz – 3400 Hz)
Corrected sigArray
Play an arbitrary column
Filtered sigArray
Apply time-delay beamforming on sigArray
Play the output signal
Compare two signals (with and without beamforming)
Output signal (N x 1)
15. 𝑥
Sound card
16 x .wav
16 x mic.
Read 16 x .wav’s into a single matrix sigArray (N x 16)
sigArray (N x 16)
Multiply each column by its corresponding
correction coefficient
Filter sigArray with a
bandpass filter (300 Hz – 3400 Hz)
Corrected sigArray
Play an arbitrary column
Filtered sigArray
Apply time-delay beamforming on sigArray
Play the output signal
Compare two signals (with and without beamforming)
Output signal (N x 1)
16. 𝑥
Sound card
16 x .wav
16 x mic.
Read 16 x .wav’s into a single matrix sigArray (N x 16)
sigArray (N x 16)
Multiply each column by its corresponding
correction coefficient
Filter sigArray with a
bandpass filter (300 Hz – 3400 Hz)
Corrected sigArray
Play an arbitrary column
Filtered sigArray
Apply time-delay beamforming on sigArray
Play the output signal
Compare two signals (with and without beamforming)
Output signal (N x 1)