Adaptive Filtering: Algorithms and Practical Implementation

Diniz, Paulo S. R.

ISBN 10: 1461441056 / ISBN 13: 9781461441052

Edité par Springer, 2012

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Page block firm and clean, binding tight, boards straight. No markings of any kind. Fine, like new condition. Well packaged and promptly shipped from California. US veteran operated. N° de réf. du vendeur 1LAGBP001BTW

Détails bibliographiques

Titre : Adaptive Filtering: Algorithms and Practical...

Éditeur : Springer

Date d'édition : 2012

Reliure : Couverture rigide

Etat : LikeNew

Edition : 4ème Édition

A propos de ce titre

Synopsis :

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.

Présentation de l'éditeur:

In its 4th edition, this book reviews basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner, covering the main classes of adaptive filtering algorithms and using clear notation to facilitate implementation.