Unsupervised Adaptive Filtering, Volume 1: Blind Source Separation

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A complete, one-stop reference on the state of the act of unsupervised adaptive filtering While unsupervised adaptive filtering has its roots in the 1960s, more recent advances in signal processing, information theory, imaging, and remote sensing have made this a hot area for research in several diverse fields. This book brings together cutting-edge information previously available only in disparate papers and articles, presenting a thorough and integrated treatment of the two major classes of algorithms used in ...
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Overview

A complete, one-stop reference on the state of the act of unsupervised adaptive filtering While unsupervised adaptive filtering has its roots in the 1960s, more recent advances in signal processing, information theory, imaging, and remote sensing have made this a hot area for research in several diverse fields. This book brings together cutting-edge information previously available only in disparate papers and articles, presenting a thorough and integrated treatment of the two major classes of algorithms used in the field, namely, blind signal separation and blind channel equalization algorithms. Divided into two volumes for ease of presentation, this important work shows how these algorithms, although developed independently, are closely related foundations of unsupervised adaptive filtering. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications in diverse fields. More than 100 illustrations as well as case studies, appendices, and references further enhance this excellent resource. Topics in Volume I include:
* Neural and information-theoretic approaches to blind signal separation
* Models, concepts, algorithms, and performance of blind source separation
* Blind separation of delayed and convolved sources
* Blind deconvolution of multipath mixtures
* Applications of blind source separation
Volume II: Blind Deconvolution continues coverage with blind channel equalization and its relationship to blind source separation.

"...deals with an intense area of research and is written by one of the foremost experts in the field...part of the Adaptive & Learning Systems for Signal Processing, Communications, & Control Series."

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Editorial Reviews

From the Publisher
"Contributions are by fore-most experts, and provides up-to-date research findings." (IEE Signal Processing Magazine, Vol. 18, No. 1, January 2001)
IEE Signal Processing Magazine
Contributions are by fore-most experts, and provides up-to-date research findings.
IEE Signal Processing Magazine
Contributions are by fore-most experts, and provides up-to-date research findings.
Booknews
Engineers from academia and industry summarize otherwise scattered information on unsupervised adaptive filtering, which has been around since the 1960s, but has become of increased interest because of developments in signal processing, information theory, imaging, and remote sensing. They focus blind signal separation and blind channel equalization algorithms as the two major classes used, and explain that though they were developed independently, they are closely related foundations of the approach to filtering. The second of two volumes covers blind deconvolution. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

Table of Contents

Introduction (S. Haykin).

Natural-Gradient Adaptation (S. Douglas & S. Amari).

Blind Signal Separation and Extraction: Neural and Information-Theoretic Approaches (S. Amari, et al.).

Entropic Contrasts for Source Separation: Geometry and Stability (J.-F. Cardoso).

Blind Source Separation: Models, Concepts, Algorithms and Performance (P. Comon & P. Chevalier).

Information Theory, Independent-Component Analysis, and Applications (A. Bell).

Information-Theoretic Learning (J. Principe, et al.).

Blind Separation of Delayed and Convolved Sources (K. Torkkola).

Blind Deconvolution of Multipath Mixtures (R. Lambert & C. Nikias).

Index.

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Sort by: Showing 1 Customer Reviews
  • Anonymous

    Posted June 8, 2001

    A Great book for this field..

    Succinct and clear explanations, broad coverages and the most recent examples like functional MRI.

    Was this review helpful? Yes  No   Report this review
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