E-Book Overview
With solid theoretical foundations and numerous potential applications, Blind Signal Processing (BSP) is one of the hottest emerging areas in Signal Processing. This volume unifies and extends the theories of adaptive blind signal and image processing and provides practical and efficient algorithms for blind source separation, Independent, Principal, Minor Component Analysis, and Multichannel Blind Deconvolution (MBD) and Equalization. Containing over 1400 references and mathematical expressions Adaptive Blind Signal and Image Processing delivers an unprecedented collection of useful techniques for adaptive blind signal/image separation, extraction, decomposition and filtering of multi-variable signals and data.
E-Book Content
Adaptive Blind Signal and Image Processing Learning Algorithms and Applications
Andrzej CICHOCKI
Shun-ichi AMARI
includes CD
Contents
Preface 1
Introduction to Blind Signal Processing: Problems and Applications 1.1 Problem Formulations – An Overview 1.1.1 Generalized Blind Signal Processing Problem 1.1.2 Instantaneous Blind Source Separation and Independent Component Analysis 1.1.3 Independent Component Analysis for Noisy Data 1.1.4 Multichannel Blind Deconvolution and Separation 1.1.5 Blind Extraction of Signals 1.1.6 Generalized Multichannel Blind Deconvolution – State Space Models 1.1.7 Nonlinear State Space Models – Semi-Blind Signal Processing 1.1.8 Why State Space Demixing Models? 1.2 Potential Applications of Blind and Semi-Blind Signal Processing 1.2.1 Biomedical Signal Processing 1.2.2 Blind Separation of Electrocardiographic Signals of Fetus and Mother 1.2.3 Enhancement and Decomposition of EMG Signals
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CONTENTS
1.2.4 1.2.5 1.2.6 1.2.7 1.2.8 2
EEG and Data MEG Processing Application of ICA/BSS for