Adaptive Filtering: Algorithms and Practical Implementation (fifth edition)
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.
2020
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.
The contents of this book include:
+ Chapter 1: Introduction to adaptive filtering
+ Chapter 2: Fundamentals of adaptive filtering
+ Chapter 3: The least-mean-square algorithm
+ Chapter 4: LMS-based algorithms
+ Chapter 5: Conventional RLS adaptive filter
+ Chapter 6: Data-selective adaptive filtering
+ Chapter 7: Adaptive lattice-based RLS algorithms
+ Chapter 8: Fast transveral RLS algorithms
+ Chapter 9: QR-Decomposition-based RLS filters
+ Chapter 10: Adaptive IIR filters
+ Chapter 11: Nonlinear adaptive filtering
+ Chapter 12: Subband adaptive filters
+ Chapter 13: Blind adative filtering
Paulo S. R. Diniz. Adaptive Filtering: Algorithms and Practical Implementation. Springer, 2020.
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