1st Edition
Unsupervised Signal Processing Channel Equalization and Source Separation
Introduction
Channel Equalization
Source Separation
Organization and Contents
Statistical Characterization of Signals and Systems
Signals and Systems
Digital Signal Processing
Probability Theory and Randomness
Stochastic Processes
Estimation Theory
Linear Optimal and Adaptive Filtering
Supervised Linear Filtering
Wiener Filtering
The Steepest-Descent Algorithm
The Least Mean Square Algorithm
The Method of Least Squares
A Few Remarks Concerning Structural Extensions
Linear Filtering without a Reference Signal
Linear Prediction Revisited
Unsupervised Channel Equalization
The Unsupervised Deconvolution Problem
Fundamental Theorems
Bussgang Algorithms
The Shalvi–Weinstein Algorithm
The Super-Exponential Algorithm
Analysis of the Equilibrium Solutions of Unsupervised Criteria
Relationships between Equalization Criteria
Unsupervised Multichannel Equalization
Systems withMultiple Inputs and/orMultiple Outputs
SIMO Channel Equalization
Methods for Blind SIMO Equalization
MIMO Channels and Multiuser Processing
Blind Source Separation
The Problem of Blind Source Separation
Independent Component Analysis
Algorithms for Independent Component Analysis
Other Approaches for Blind Source Separation
Convolutive Mixtures
Nonlinear Mixtures
Nonlinear Filtering and Machine Learning
Decision-Feedback Equalizers
Volterra Filters
Equalization as a Classification Task
Artificial Neural Network
Bio-Inspired Optimization Methods
Why Bio-Inspired Computing?
Genetic Algorithms
Artificial Immune Systems
Particle Swarm Optimization
Appendix A: Some Properties of the Correlation Matrix
Appendix B: Kalman Filter
References
Index
Biography
João Marcos Travassos Romano is a professor at the University of Campinas (UNICAMP), Campinas, Sao Paulo, Brazil. He received his BS and MS in electrical engineering from UNICAMP in 1981 and 1984, respectively. In 1987, he received his Ph.D from the University of Paris–XI, Orsay. He has been an invited professor at CNAM, Paris; at University of Paris–Descartes; and at ENS, Cachan. He is the coordinator of the DSPCom Laboratory at UNICAMP, and his research interests include adaptive filtering, unsupervised signal processing, and applications in communication systems.
Romis Ribeiro de Faissol Attux is an assistant professor at the University of Campinas (UNICAMP), Campinas, Sao Paulo, Brazil. He received his BS, MS, and Ph.D in electrical engineering from UNICAMP in 1999, 2001, and 2005, respectively. He is a researcher in the DSPCom Laboratory. His research interests include blind signal processing, independent component analysis (ICA), nonlinear adaptive filtering, information-theoretic learning, neural networks, bio-inspired computing, dynamical systems, and chaos.
Charles Casimiro Cavalcante is an assistant professor at the Federal University of Ceará (UFC), Fortaleza, Ceara, Brazil. He received his BSc and MSc in electrical engineering from UFC in 1999 and 2001, respectively, and his Ph.D from the University of Campinas, Campinas, Sao Paulo, Brazil, in 2004. He is a researcher in the Wireless Telecommunications Research Group (GTEL), where he leads research on signal processing for communications, blind source separation, wireless communications, and statistical signal processing.
Ricardo Suyama is an assistant professor at the Federal University of ABC (UFABC), Santo Andre, Sao Paulo, Brazil. He received his BS, MS, and Ph.D in electrical engineering from the University of Campinas, Campinas, Sao Paulo, Brazil in 2001, 2003, and 2007, respectively. He is a researcher in the DSPCom Laboratory at UNICAMP. His research interests include adaptive filtering, source separation, and applications in communication systems.
