Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications

Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications

Author(s): Andrzej Cichocki, Shun-ichi Amari

Published Online: 17 JUL 2002

Print ISBN: 9780471607915

Online ISBN: 9780470845899

DOI: 10.1002/0470845899

About this Book

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 provided
MATLAB(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.

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