Description |
MATLAB files to implement all Adaptive Filtering Algorithms in the book by Paulo S. R. Diniz, Adaptive Filtering Algorithms and Practical Implementation, Fourth Edition, Springer, New York, 2013.
This book 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.
In the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S.R. Diniz presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. The main classes of adaptive filtering algorithms are presented in a unified framework, using clear notations that facilitate actual implementation.
The main algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Many examples address problems drawn from actual applications. New material to this edition includes:
- Analytical and simulation examples in Chapters 4, 5, 6 and 10
- Appendix E, which summarizes the analysis of set-membership algorithm
- Updated problems and references
Providing a concise background on adaptive filtering, this book covers the family of LMS, affine projection, RLS and data-selective set-membership algorithms as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more.
Several problems are included at the end of chapters, and some of these problems address applications. A user-friendly MATLAB package is provided where the reader can easily solve new problems and test algorithms in a quick manner.
An instructor`s manual, a set of master transparences, and MATLAB codes for all of the algorithms described in the text are also available. Useful to both professional researchers and students, the text includes hundreds of problems, numerous examples, and over 150 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.
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