1st Edition

Signals and Images Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing

    628 Pages
    by CRC Press

    628 Pages 32 Color & 168 B/W Illustrations
    by CRC Press

    628 Pages 32 Color & 168 B/W Illustrations
    by CRC Press

    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.

    THEORY AND METHODS
    Rosângela Fernandes Coelho and Vítor 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
    Rosângela Fernandes Coelho and Vítor 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
    João 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
    João 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

    Biography

    Rosângela Fernandes Coelho, Vitor Heloiz Nascimento, Ricardo Lopes de Queiroz, João Marcos Travassos Romano, Charles Casimiro Cavalcante

    "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."
    —Jerónimo Arenas-García, 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, Brazil