Unsupervised Adaptive Filtering: Blind Source Separation v. 1
Published on 14. April 2000
Book
Hardback
446 pages
978-0-471-29412-2 (ISBN)
Description
Unsupervised adaptive filters let systems respond and adapt automatically to changing conditions without the need for human supervision. With applications to signal processing, information theory, imaging, and remote sensing, among others, this is an area of intense research. This book describes the current state of the art in the field.
Reviews / Votes
"Contributions are by fore-most experts, and provides up-to-date research findings." (IEE Signal Processing Magazine, Vol. 18, No. 1, January 2001)More details
Series
Edition
Volume 1 ed.
Language
English
Place of publication
New York
United States
Publishing group
John Wiley and Sons Ltd
Target group
College/higher education
Professional and scholarly
Illustrations
Ill.
Dimensions
Height: 242 mm
Width: 162 mm
Thickness: 27 mm
Weight
766 gr
ISBN-13
978-0-471-29412-2 (9780471294122)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Content
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.