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Adaptive Filtering - Algorithms and Practical Implementation (Paperback, 5th ed. 2020)
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Adaptive Filtering - Algorithms and Practical Implementation (Paperback, 5th ed. 2020)
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In the fifth edition of this textbook, author Paulo S.R. Diniz
presents updated text on the basic concepts of adaptive signal
processing and adaptive filtering. He first introduces the main
classes of adaptive filtering algorithms in a unified framework,
using clear notations that facilitate actual implementation.
Algorithms are described in tables, which are detailed enough to
allow the reader to verify the covered concepts. Examples address
up-to-date problems drawn from actual applications. Several
chapters are expanded and a new chapter 'Kalman Filtering' is
included. The book provides a concise background on adaptive
filtering, including the family of LMS, affine projection, RLS,
set-membership algorithms and Kalman filters, as well as nonlinear,
sub-band, blind, IIR adaptive filtering, and more. Problems are
included at the end of chapters. A MATLAB package is provided so
the reader can solve new problems and test algorithms. The book
also offers easy access to working algorithms for practicing
engineers.
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