Signals and Images

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Opis: Signals and Images

Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing cohesively combines contributions from field experts to deliver a comprehensive account of the latest developments in signal processing. These experts detail the results of their research related to audio and speech enhancement, acoustic image estimation, video compression, biometric recognition, hyperspectral image analysis, tensor decomposition with applications in communications, adaptive sparse-interpolated filtering, signal processing for power line communications, bio-inspired signal processing, seismic data processing, arithmetic transforms for spectrum computation, particle filtering in cooperative networks, three-dimensional television, and more. This book not only shows how signal processing theory is applied in current and emerging technologies, but also demonstrates how to tackle key problems such as how to enhance speech in the time domain, improve audio quality, and meet the desired electrical consumption target for controlling carbon emissions. Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing serves as a guide to the next generation of signal processing solutions for speech and video coding, hearing aid devices, big data processing, smartphones, smart digital communications, acoustic sensors, and beyond. "In today's society, signal processing serves as the core component for many ubiquitous technologies essential to our everyday lives, including smartphones, digital cameras, wearable devices, IMAX 3D movies, and HD TVs. The authors present a wonderfully informative investigation into the theory and methods underlying such technologies, particularly in acoustic signal processing, image processing, signal processing in communications, and various other vital signal processing topics. Despite the rapidly changing nature of signal processing, the authors present the perfect, expert guide for undergraduate and graduates students, researchers, and practitioners to understand and develop the next generation of crucial emerging signal processing technologies." -Marek Trawicki, Marquette University, Milwaukee, Wisconsin, USA "... covers some of the most significant recent advances in signal processing, including methods and applications. Chapters are written in a tutorial style and are ideal both for researchers of the field or close fields who want to get a deeper insight into the covered materials and for early-stage researchers who need to obtain a global overview of signal processing problems to define their own interests." -Jeronimo Arenas-Garcia, Universidad Carlos III de Madrid, Spain "... aids the reader in getting acquainted with many subjects of high interest in a fast and convenient manner. Written by experts in the covered fields, the book is a very valuable addition to the literature." -Paulo S. R. Diniz, Federal University of Rio de Janeiro, BrazilTHEORY AND METHODS Rosangela Fernandes Coelho and Vitor Heloiz Nascimento Blind Source Separation: Principles of Independent and Sparse Component Analysis Introduction The Blind Source Separation Problem BSS Methods Based on Independent Component Analysis BSS Methods Based on Sparse Component Analysis Conclusions Kernel-Based Nonlinear Signal Processing Chapter Summary Introduction Reproducing Kernel Hilbert Spaces (RKHS) Nonlinear Regression in an RKHS Online Kernel-Based Function Approximation Online Nonlinear System Identification Bayesian Approaches to Kernel-Based Nonlinear Regression Conclusion Arithmetic Transforms: Theory, Advances, and Challenges Introduction Historical Context Mathematical Background Arithmetic Fourier Transform Arithmetic Hartley Transform Arithmetic Cosine Transform Arithmetic Transform Interpolation Discussion and Conclusion Appendix: Dirichlet inverse of {(-1)n} Distributed Particle Filtering in Cooperative Networks Introduction Cooperative Particle Filtering with Multiple Observers Distributed Particle Filters Cooperative Emitter Tracking using Passive Sensors Cooperative Equalization of Digital Communication Channels Conclusions Appendix I Appendix II ACOUSTIC SIGNAL PROCESSING Rosangela Fernandes Coelho and Vitor Heloiz Nascimento Empirical Mode Decomposition Theory Applied to Speech Enhancement Introduction Empirical Mode Decomposition Speech Enhancement EMD-Based Speech Enhancement Results Conclusion Acoustic Imaging Using the Kronecker Array Transform Introduction Signal Model Methods for Acoustic Imaging Kronecker Array Transform Computional Cost Examples Practical Considerations Conclusion Automatic Evaluation of Acoustically Degraded Full-Band Speech Introduction Highlighted Standards and References Models for Telepresence System Quality Evaluation Tools Degradation Type Classification Concluding Remarks Models for Speech Processing Introduction Time-Frequency Models Production Models Linear Prediction Spectral Representations and Models Stochastic Models Time-Varying Models Acknowledgment IMAGE PROCESSING Ricardo Lopes de Queiroz Energy-Aware Video Compression Introduction Background on H.264/AVC Implementation Our H.264/AVC Test Systems Power and Energy in Computing Systems Energy vs. Complexity Energy-Aware Optimization Results Conclusions Rotation and Scale Invariant Template Matching Introduction Conventional BC-Invariant Template Matching Brute Force RSTBC-Invariant Template Matching Ciratefi: RSTBC-Invariant Template Matching Forapro: RTBC-Invariant Template Matching with Robustness to Scaling Conclusions Three-Dimensional Television (3DTV) 3D Basics 3D Compression Conclusions SIGNAL PROCESSING IN COMMUNICATIONS Joao Marcos Travassos Romano and Charles Casimiro Cavalcante Overview of Tensor Decompositions with Applications to Communications Introduction Notations Tensor Models Application to MIMO Communication Systems Application to Cooperative Communications Application to Multidimensional Array Processing Summary Signal Detection and Parameter Estimation in Massive MIMO Systems Introduction Signal Models and Application Scenarios Detection Techniques Parameter Estimation Techniques Simulation Results Future Trends and Emerging Topics Concluding Remarks Advances on Adaptive Sparse-Interpolated Filtering Introduction From the FIR Filter to the Sparse-Interpolated FIR Filter Adaptive Sparse-Interpolated FIR Filters Adaptive Sparse-Interpolated Volterra Filters A Case Study of Network Echo Cancellation Concluding Remarks Cognitive Power Line Communication Introduction Cognitive PLC Spectrum Sensing Techniques Spectrum Sensing Techniques for CogPLC Future Trends Conclusions SELECTED TOPICS IN SIGNAL PROCESSING Joao Marcos Travassos Romano and Charles Casimiro Cavalcante Information Geometry: An Introduction to New Models for Signal Processing Introduction Statistical Manifolds Generalized Statistical Manifolds Geometry of (Generalized) Statistical Manifolds Summary and Research Directions Brief Introduction to Riemannian Geometry Bio-Inspired and Information-Theoretic Signal Processing Introduction Artificial Neural Networks Information Theoretic Learning Bio-Inspired Optimization Concluding Remarks High-Resolution Techniques for Seismic Signal Prospecting Introduction Summary High-Resolution Velocity Spectra Event Detection Schemes for Seismic Data Analysis 2D Deconvolution Conclusion Synthetic Aperture Imaging for Ultrasonic Non-Destructive Testing Beamforming in Ultrasonic Array Imaging Systems Instantaneous Phase Information to Improve Defect Detection Simplified Process for Synthetic Aperture Imaging Experimental Results Comments


Szczegóły: Signals and Images

Tytuł: Signals and Images
Producent: Productivity Press Inc
ISBN: 9781498722360
Rok produkcji: 2015
Ilość stron: 628
Oprawa: Twarda
Waga: 1.34 kg


Recenzje: Signals and Images

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Signals and Images

Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing cohesively combines contributions from field experts to deliver a comprehensive account of the latest developments in signal processing. These experts detail the results of their research related to audio and speech enhancement, acoustic image estimation, video compression, biometric recognition, hyperspectral image analysis, tensor decomposition with applications in communications, adaptive sparse-interpolated filtering, signal processing for power line communications, bio-inspired signal processing, seismic data processing, arithmetic transforms for spectrum computation, particle filtering in cooperative networks, three-dimensional television, and more. This book not only shows how signal processing theory is applied in current and emerging technologies, but also demonstrates how to tackle key problems such as how to enhance speech in the time domain, improve audio quality, and meet the desired electrical consumption target for controlling carbon emissions. Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing serves as a guide to the next generation of signal processing solutions for speech and video coding, hearing aid devices, big data processing, smartphones, smart digital communications, acoustic sensors, and beyond. "In today's society, signal processing serves as the core component for many ubiquitous technologies essential to our everyday lives, including smartphones, digital cameras, wearable devices, IMAX 3D movies, and HD TVs. The authors present a wonderfully informative investigation into the theory and methods underlying such technologies, particularly in acoustic signal processing, image processing, signal processing in communications, and various other vital signal processing topics. Despite the rapidly changing nature of signal processing, the authors present the perfect, expert guide for undergraduate and graduates students, researchers, and practitioners to understand and develop the next generation of crucial emerging signal processing technologies." -Marek Trawicki, Marquette University, Milwaukee, Wisconsin, USA "... covers some of the most significant recent advances in signal processing, including methods and applications. Chapters are written in a tutorial style and are ideal both for researchers of the field or close fields who want to get a deeper insight into the covered materials and for early-stage researchers who need to obtain a global overview of signal processing problems to define their own interests." -Jeronimo Arenas-Garcia, Universidad Carlos III de Madrid, Spain "... aids the reader in getting acquainted with many subjects of high interest in a fast and convenient manner. Written by experts in the covered fields, the book is a very valuable addition to the literature." -Paulo S. R. Diniz, Federal University of Rio de Janeiro, BrazilTHEORY AND METHODS Rosangela Fernandes Coelho and Vitor Heloiz Nascimento Blind Source Separation: Principles of Independent and Sparse Component Analysis Introduction The Blind Source Separation Problem BSS Methods Based on Independent Component Analysis BSS Methods Based on Sparse Component Analysis Conclusions Kernel-Based Nonlinear Signal Processing Chapter Summary Introduction Reproducing Kernel Hilbert Spaces (RKHS) Nonlinear Regression in an RKHS Online Kernel-Based Function Approximation Online Nonlinear System Identification Bayesian Approaches to Kernel-Based Nonlinear Regression Conclusion Arithmetic Transforms: Theory, Advances, and Challenges Introduction Historical Context Mathematical Background Arithmetic Fourier Transform Arithmetic Hartley Transform Arithmetic Cosine Transform Arithmetic Transform Interpolation Discussion and Conclusion Appendix: Dirichlet inverse of {(-1)n} Distributed Particle Filtering in Cooperative Networks Introduction Cooperative Particle Filtering with Multiple Observers Distributed Particle Filters Cooperative Emitter Tracking using Passive Sensors Cooperative Equalization of Digital Communication Channels Conclusions Appendix I Appendix II ACOUSTIC SIGNAL PROCESSING Rosangela Fernandes Coelho and Vitor Heloiz Nascimento Empirical Mode Decomposition Theory Applied to Speech Enhancement Introduction Empirical Mode Decomposition Speech Enhancement EMD-Based Speech Enhancement Results Conclusion Acoustic Imaging Using the Kronecker Array Transform Introduction Signal Model Methods for Acoustic Imaging Kronecker Array Transform Computional Cost Examples Practical Considerations Conclusion Automatic Evaluation of Acoustically Degraded Full-Band Speech Introduction Highlighted Standards and References Models for Telepresence System Quality Evaluation Tools Degradation Type Classification Concluding Remarks Models for Speech Processing Introduction Time-Frequency Models Production Models Linear Prediction Spectral Representations and Models Stochastic Models Time-Varying Models Acknowledgment IMAGE PROCESSING Ricardo Lopes de Queiroz Energy-Aware Video Compression Introduction Background on H.264/AVC Implementation Our H.264/AVC Test Systems Power and Energy in Computing Systems Energy vs. Complexity Energy-Aware Optimization Results Conclusions Rotation and Scale Invariant Template Matching Introduction Conventional BC-Invariant Template Matching Brute Force RSTBC-Invariant Template Matching Ciratefi: RSTBC-Invariant Template Matching Forapro: RTBC-Invariant Template Matching with Robustness to Scaling Conclusions Three-Dimensional Television (3DTV) 3D Basics 3D Compression Conclusions SIGNAL PROCESSING IN COMMUNICATIONS Joao Marcos Travassos Romano and Charles Casimiro Cavalcante Overview of Tensor Decompositions with Applications to Communications Introduction Notations Tensor Models Application to MIMO Communication Systems Application to Cooperative Communications Application to Multidimensional Array Processing Summary Signal Detection and Parameter Estimation in Massive MIMO Systems Introduction Signal Models and Application Scenarios Detection Techniques Parameter Estimation Techniques Simulation Results Future Trends and Emerging Topics Concluding Remarks Advances on Adaptive Sparse-Interpolated Filtering Introduction From the FIR Filter to the Sparse-Interpolated FIR Filter Adaptive Sparse-Interpolated FIR Filters Adaptive Sparse-Interpolated Volterra Filters A Case Study of Network Echo Cancellation Concluding Remarks Cognitive Power Line Communication Introduction Cognitive PLC Spectrum Sensing Techniques Spectrum Sensing Techniques for CogPLC Future Trends Conclusions SELECTED TOPICS IN SIGNAL PROCESSING Joao Marcos Travassos Romano and Charles Casimiro Cavalcante Information Geometry: An Introduction to New Models for Signal Processing Introduction Statistical Manifolds Generalized Statistical Manifolds Geometry of (Generalized) Statistical Manifolds Summary and Research Directions Brief Introduction to Riemannian Geometry Bio-Inspired and Information-Theoretic Signal Processing Introduction Artificial Neural Networks Information Theoretic Learning Bio-Inspired Optimization Concluding Remarks High-Resolution Techniques for Seismic Signal Prospecting Introduction Summary High-Resolution Velocity Spectra Event Detection Schemes for Seismic Data Analysis 2D Deconvolution Conclusion Synthetic Aperture Imaging for Ultrasonic Non-Destructive Testing Beamforming in Ultrasonic Array Imaging Systems Instantaneous Phase Information to Improve Defect Detection Simplified Process for Synthetic Aperture Imaging Experimental Results Comments

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Cena 655,00 PLN
Nasza cena 612,42 PLN
Oszczędzasz 6%
Wysyłka: Niedostępna
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Szczegóły: Signals and Images

Tytuł: Signals and Images
Producent: Productivity Press Inc
ISBN: 9781498722360
Rok produkcji: 2015
Ilość stron: 628
Oprawa: Twarda
Waga: 1.34 kg


Recenzje: Signals and Images

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