Adaptive Filtering: Algorithms and Practical Implementation, Edition 2

Paulo S.R. Diniz

2013. g. marts · The Springer International Series in Engineering and Computer Science 694. grāmata · Springer Science & Business Media

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Adaptive Filtering: Algorithms and Practical Implementation, Second Edition, presents a concise overview of adaptive filtering, covering as many algorithms as possible in a unified form that avoids repetition and simplifies notation. It is suitable as a textbook for senior undergraduate or first-year graduate courses in adaptive signal processing and adaptive filters. The philosophy of the presentation is to expose the material with a solid theoretical foundation, to concentrate on algorithms that really work in a finite-precision implementation, and to provide easy access to working algorithms. Hence, practicing engineers and scientists will also find the book to be an excellent reference.
This second edition contains a substantial amount of new material:

-Two new chapters on nonlinear and subband adaptive filtering;
-Linearly constrained Weiner filters and LMS algorithms;
-LMS algorithm behavior in fast adaptation;
-Affine projection algorithms;
-Derivation smoothing;
-MATLAB codes for algorithms.

An instructor's manual, a set of master transparencies, and the MATLAB codes for all of the algorithms described in the text are also available.
Useful to both professional researchers and students, the text includes 185 problems; over 38 examples, and over 130 illustrations. It is of primary interest to those working in signal processing, communications, and circuits and systems. It will also be of interest to those working in power systems, networks, learning systems, and intelligent systems.