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Engineering - Signals & Communication | Adaptive Filtering - Algorithms and Practical Implementation

Adaptive Filtering

Algorithms and Practical Implementation

Diniz, Paulo S. R.

Originally published as volume 694 in the series: The International Series in Engineering and Computer Science

3rd ed. 2008, XXIV, 627 p.

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  • Includes a unique chapter on adaptive IIR filters.
  • Contains two new chapters on Data-Selective and Blind adaptive filtering.
  • Expands on the discussion on linear-constrained Wiener filter from the second edition.
  • Includes a deeper treatment of complex algorithms.
  • Shows a detailed analysis of the affine projection algorithm.
  • The concept of Kalman filtering is included in Appendix D as complement of Chapter 5.
  • Includes many new examples, especially in the early chapters as well as a solutions manual for instructors.
  • A user friendly MATLAB package is available on the book's web page (http://www.lps.ufrj.br/profs/diniz/adaptivebook/) where the reader can easily solve new problems and test all algorithms included in the book.

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.

Content Level » Graduate

Keywords » Signal - algorithm - filter - integrated circuit - micro-alloy transistor - single-electron transistor - static-induction transistor - tables

Related subjects » Circuits & Systems - Complexity - Electronics & Electrical Engineering - Robotics - Signals & Communication

Table of contents 

To Adaptive Filtering.- Fundamentals of Adaptive Filtering.- The Least-Mean-Square (LMS) Algorithm.- Lms-Based Algorithms.- Conventional Rls Adaptive Filter.- Data-Selective Adaptive Filtering.- Adaptive Lattice-Based Rls Algorithms.- Fast Transversal Rls Algorithms.- Qr-Decomposition-Based Rls Filters.- Adaptive Iir Filters.- Nonlinear Adaptive Filtering.- Subband Adaptive Filters.- Blind Adaptive Filtering.

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