Adaptive Filtering Algorithms and Implementations (Second Edition)

Author: (English) Dini, translated by Liu Yulin et al.
Publisher:
Publishing Date: 2004-07-01
Features: This book concisely introduces adaptive filtering theory in a unified form, encompassing as many algorithms as possible while avoiding repetition and complex notation. The guiding principle of the book is to reveal the solid theoretical foundation of adaptive filtering, with a focus on discussing algorithms that can truly be effective with finite-precision implementations. The second edition of this book, based on the first edition, adds entirely new content and research findings, including nonlinear adaptive filtering, subband adaptive filtering, linear constrained Wiener filters, behavior analysis of LMS algorithms in fast adaptive implementations, and affine projection algorithms. Additionally, according to teaching needs and reader requests, the author has adjusted and optimized some content in the book. The book provides numerous algorithms, examples, simulation results, and references to help readers deeply understand the material. Readers of this book are expected to have a grasp of some basic principles of digital signal processing and stochastic processes. It is suitable as a textbook for senior undergraduate and graduate students in signal processing, communications, circuits and systems, intelligent systems, and related fields, as well as a reference book for researchers in related disciplines.