Adaptive Filtering

Algorithms and Practical Implementation

Nonfiction, Science & Nature, Technology, Electronics, Circuits
Cover of the book Adaptive Filtering by Paulo S. R. Diniz, Springer US
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Author: Paulo S. R. Diniz ISBN: 9781461441069
Publisher: Springer US Publication: August 14, 2012
Imprint: Springer Language: English
Author: Paulo S. R. Diniz
ISBN: 9781461441069
Publisher: Springer US
Publication: August 14, 2012
Imprint: Springer
Language: English

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. Additionally, the book provides easy access to working algorithms for practicing engineers.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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:

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. Additionally, the book provides easy access to working algorithms for practicing engineers.

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