1.

Record Nr.

UNINA9910437882903321

Autore

Diniz Paulo S. R

Titolo

Adaptive Filtering : Algorithms and Practical Implementation / / by Paulo S. R. Diniz

Pubbl/distr/stampa

New York, NY : , : Springer US : , : Imprint : Springer, , 2013

ISBN

1-4614-4106-4

Edizione

[4th ed. 2013.]

Descrizione fisica

1 online resource (661 p.)

Disciplina

621.3822

Soggetti

Signal processing

Image processing

Speech processing systems

Electronic circuits

Electrical engineering

Automatic control

Signal, Image and Speech Processing

Circuits and Systems

Communications Engineering, Networks

Electrical Engineering

Control and Systems Theory

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Introduction 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.

Sommario/riassunto

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.