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"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."
"Adaptive Filtering: Algorithms and Practical Implementation is a concise presentation of adaptive filtering, covering as many algorithms as possible while avoiding adapting notations and derivations related to the different algorithms. Furthermore, the book points out the algorithms which really work in a finite-precision implementation, and provides easy access to the working algorithms for the practicing engineer. Adaptive Filtering: Algorithms and Practical Implementation may be used as the principle text for courses on the subject, and serves as an excellent reference for professional engineers and researchers in the field."
"The field of digital signal processing has developed considerably in the last two decades. This development is related to the growth of available technologies for implementing digital signal processing algorithms. If accurate information on the signals to be processed is available, the designer can easily choose the most appropriate algorithm to process the signal. Fixed algorithms do not process efficiently signals whose statistical properties are unknown. The solution is to use an adaptive filter that automatically changes its characteristics by optimizing its internal parameters. Adaptive filtering algorithms are essential in many statistical signal processing applications. Adaptive Filtering: Algorithms and Practical Implementation is a concise presentation of adaptive filtering, covering as many algorithms as possible while avoiding adapting notations and derivations related to the different algorithms. Furthermore, the book points out the algorithms which really work in a finite-precision implementation, and provides easy access to the working algorithms for the practicing engineer. Adaptive Filtering: Algorithms and Practical Implementation may be used as the principal text for courses on the subject, and serves as an excellent reference for professional engineers and researchers in the field. The author has prepared master transparencies, Matlab routines and an errata file for the book which may be obtained via ftp as follows: ftp lps.ufrj.br login: anonymous password: your email address cd /staff/diniz/pub."
"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 10Appendix E, which summarizes the analysis of set-membership algorithmUpdated problems and referencesProviding 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."@en
"Presents the basic concepts of adaptive signal processing and adaptive filtering. This book covers the family of LMS and algorithms as well as set-membership, sub-band, blind, and IIR adaptive filtering."@en
"Adaptive Filtering: Algorithms and Practical Implementation, Second Edition, 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. This second edition contains a substantial amount of new material: -Two new chapters on nonlinear and subband adaptive filtering; -Linearly constrained Weiner filters and LMS algorithms; -LMS algorithm behavior in fast adaptation; -Affine projection algorithms; -Derivation smoothing; -MATLAB codes for algorithms."

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"Adaptive Filtering : Algorithms and Practical Implementation"
"Adaptive filtering : Algorithms and practical implementation"
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"Adaptive filtering algorithms and practical implementation"@en
"Adaptive filtering algorithms and practical implementation"
"Adaptive filtering : algorithms and practical implementation"@en
"Adaptive filtering : algorithms and practical implementation"
"Adaptive Filtering Algorithms and Practical Implementation"@en
"Adaptive Filtering Algorithms and Practical Implementation"

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