Adaptive blind signal and image processing

✍ Scribed by Cichocki A., Amari S.-i.

• Publisher: Wiley
• Year: 2002
• Tongue: English
• Leaves: 587
• Category: Library

✦ Synopsis

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. Offers a broad coverage of blind signal processing techniques and algorithms both from a theoretical and practical point of view Presents more than 50 simple algorithms that can be easily modified to suit the reader's specific real world problems Provides a guide to fundamental mathematics of multi-input, multi-output and multi-sensory systems Includes illustrative worked examples, computer simulations, tables, detailed graphs and conceptual models within self contained chapters to assist self study* Accompanying CD-ROM features an electronic, interactive version of the book with fully coloured figures and text. C and MATLAB(r) user-friendly software packages are also providedMATLAB(r) is a registered trademark of The MathWorks, Inc.By providing a detailed introduction to BSP, as well as presenting new results and recent developments, this informative and inspiring work will appeal to researchers, postgraduate students, engineers and scientists working in biomedical engineering,communications, electronics, computer science, optimisations, finance, geophysics and neural networks.

✦ Table of Contents

Contents......Page 5
List of Figures......Page 17
List of Tables......Page 27
Preface......Page 29
1. Introduction......Page 33
2. Algebraic Equations Hs=x......Page 75
3. PCA/MCA......Page 119
4. Blind Decorrelation, SOS BSS......Page 161
5. Blind Source Extraction......Page 209
6. Natural Gradient Approach to ICA......Page 263
7. Locally Adaptive Algorithms for ICA/BSS......Page 305
8. ICA for Noisy Data......Page 337
9. Multichannel Blind Deconvolutio, Equalization and Separation......Page 367
10. Superefficiency, Estimating Functions......Page 415
11. State Space Models for Blind Filtering......Page 455
12. Nonlinear State Space Models: Semi-Blind SP......Page 475
Appendix:Matrix Differential Calculus......Page 485
REFERENCES......Page 497
Symbols......Page 579
Index......Page 584