Adaptive Filtering: Algorithms And Practical Implementation, 3Rd Edition

Paulo S R Diniz

ISBN 10: 0387312749 / ISBN 13: 9780387312743

Published by Springer, 2008

About this Item

New.SoftCover International edition. Different ISBN and Cover image but contents are same as US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Seller Inventory # ABEJUNE24-276186

Bibliographic Details

Title: Adaptive Filtering: Algorithms And Practical...

Publisher: Springer

Publication Date: 2008

Binding: Soft cover

Condition: Brand New

Edition: 3rd Edition, International Edition

About this title

Synopsis:

This book presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner, using clear notations that facilitate actual implementation. Important algorithms are described in detailed tables which allow the reader to verify learned concepts. The book covers the family of LMS and algorithms as well as set-membership, sub-band, blind, IIR adaptive filtering, and more. The book is also supported by a web page maintained by the author.

From the Back Cover:

Adaptive Filtering: Algorithms and Practical Implementation, Third Edition, presents basic concepts of adaptive signal processing and filtering in a concise and straightforward manner. It concentrates on on-line algorithms whose adaptation occurs whenever a new sample of each environment signal is available. The material also illustrates block algorithms using a sub-band filtering framework whose adaptation occurs when a new block of data is available. Highlights of the new edition include: Expanded treatment of complex algorithms throughout the book New chapters on Data-Selective and Blind Adaptive Filtering An enlarged discussion of linear-constrained Wiener filters Detailed analysis of the affine projection algorithm Updated derivations and many new examples A primer on Kalman filtering in Appendix D as a complement to RLS algorithms. Algorithms are presented in a unified framework using a consistent notation that facilitates their actual implementation. The main algorithms are summarized and described in tables. Many examples address problems drawn from actual applications. The family of LMS and RLS algorithms as well as set-membership, sub-band, blind, nonlinear and IIR adaptive filtering, are covered. Problems are included at the end of chapters. Adaptive Filtering: Algorithms and Practical Implementation, Third Edition, is intended for advanced undergraduate and graduate students studying adaptive filtering and will also serve as an up-to-date and useful reference for professional engineers working in the field.