Adaptive Filtering
Algorithms and Practical Implementation
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Beschreibung
Adaptive Filtering: Algorithms and Practical Implementation, Third Edition, presents basic concepts of adaptive signal processing and filtering in a concise and straightforward manner. It concentrates on on-line algorithms whose adaptation occurs whenever a new sample of each environment signal is available. The material also illustrates block algorithms using a sub-band filtering framework whose adaptation occurs when a new block of data is available.
Highlights of the new edition include:
Expanded treatment of complex algorithms throughout the book
New chapters on Data-Selective and Blind Adaptive Filtering
An enlarged discussion of linear-constrained Wiener filters
Detailed analysis of the affine projection algorithm
Updated derivations and many new examples
A primer on Kalman filtering in Appendix D as a complement to RLS algorithms.
Algorithms are presented in a unified framework using a consistent notation that facilitates their actual implementation. The main algorithms are summarized and described in tables. Many examples address problems drawn from actual applications. The family of LMS and RLS algorithms as well as set-membership, sub-band, blind, nonlinear and IIR adaptive filtering, are covered. Problems are included at the end of chapters.
Adaptive Filtering: Algorithms and Practical Implementation, Third Edition, is intended for advanced undergraduate and graduate students studying adaptive filtering and will also serve as an up-to-date and useful reference for professional engineers working in the field.
This book presents basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner.
The field of Digital Signal Processing has developed so fast in the last three decades that it can be found in the graduate and undergraduate programs of most universities. This development is related to the increasingly available technologies for implementing digital signal processing algorithms. The tremendous growth of development in the digital signal processing area has turned some of its specialized areas into fields themselves. If accurate information of the signals to be processed is available, the designer call easily choose the most appropriate algorithm to process the signal. When dealing with signals whose statistical properties are unknown, fixed algorithms do not process these signals efficiently. The solution is to use an adaptive filter that automatically changes its characteristics by optimizing the internal parameters. The adaptive filtering algorithms are essential in many statistical signal processing applications. Although the field of adaptive signal processing has been subject of research for over four decades, it was in the eighties that a major growth occurred in research and applications. Two main reasons can be credited to this growth, the availability of implementation tools and the appearance of early textbooks exposing the subject in an organized manner. Still today it is possible to observe many research developments in the area of adaptive filtering, particularly addressing specific applications.
Includes a unique chapter on adaptive IIR filters.
Contains two new chapters on Data-Selective and Blind adaptive filtering.
Expands on the discussion on linear-constrained Wiener filter from the second edition.
Includes a deeper treatment of complex algorithms.
Shows a detailed analysis of the affine projection algorithm.
The concept of Kalman filtering is included in Appendix D as complement of Chapter 5.
Includes many new examples, especially in the early chapters as well as a solutions manual for instructors.
A user friendly MATLAB package is available on the book's web page (http://www.lps.ufrj.br/profs/diniz/adaptivebook/) where the reader can easily solve new problems and test all algorithms included in the book.
This book 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 introduced in a unifed framework, using clear notations that facilitate actual implementation. The most important algorithms are described in detailed tables which allow the reader to verify learned concepts. Many examples address problems drawn from actual applications. The book covers the family of LMS and algorithms as well as set-membership, sub-band, blind, IIR adaptive filtering, and more. A user-friendly MATLAB package enables the reader to easily solve new problems and quickly test all of the algorithms. The book also provides access to algorithms for practicing engineers. The book is also supported by a web page maintained by the author.
Autor*in
Paulo S. R. Diniz
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From the reviews of the third edition:"This text concentrates on studying on-line algorithms, those whose adaptation occurs whenever a new sample of each environment signal is available. … This edition also includes basic introductions to nonlinear adaptive filtering and blind signal processing as natural extensions of the algorithms … . The book is of great importance for digital signal processing undergraduate and graduate courses in universities." (George S. Stavrakakis, Zentralblatt MATH, Vol. 1155, 2009)"The book titled ‘Adaptive Filtering: Algorithms and Practical Implementation,’ Third Edition, by Paulo S. R. Diniz replaces two previous editions. This new edition has improved significantly upon those two editions. … The book is also very practical. To attest to its suitability as a teaching text, the author has given a number of carefully developed examples which are useful … to students. … Overall, the book is excellent for teaching the subject of adaptive signal processing and enhances the landscape of textbooks on the subject." (Tokunbo Ogunfunmi, IEEE Communications Magazine, October, 2009)
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