TY - BOOK ID - 14306199 TI - A rapid introduction to adaptive filtering AU - Vega, Leonardo Rey. AU - Rey, Hernan. PY - 2012 SN - 21918112 SN - 364230298X 9786613924568 3642302998 1283612119 PB - Berlin ; New York : Springer, DB - UniCat KW - Adaptive filters. KW - Adaptive signal processing. KW - Radio frequency modulation, Narrow-band. KW - Electrical & Computer Engineering KW - Engineering & Applied Sciences KW - Electrical Engineering KW - Applied Physics KW - Telecommunications KW - Algorithms. KW - Engineering. KW - Artificial intelligence. KW - Computational intelligence. KW - Signal, Image and Speech Processing. KW - Artificial Intelligence (incl. Robotics). KW - Computational Intelligence. KW - Intelligence, Computational KW - Artificial intelligence KW - Soft computing KW - AI (Artificial intelligence) KW - Artificial thinking KW - Electronic brains KW - Intellectronics KW - Intelligence, Artificial KW - Intelligent machines KW - Machine intelligence KW - Thinking, Artificial KW - Bionics KW - Cognitive science KW - Digital computer simulation KW - Electronic data processing KW - Logic machines KW - Machine theory KW - Self-organizing systems KW - Simulation methods KW - Fifth generation computers KW - Neural computers KW - Construction KW - Industrial arts KW - Technology KW - Algorism KW - Algebra KW - Arithmetic KW - Filters, Adaptive KW - Electric filters KW - Foundations KW - Artificial Intelligence. KW - Signal processing. KW - Image processing. KW - Speech processing systems. KW - Computational linguistics KW - Electronic systems KW - Information theory KW - Modulation theory KW - Oral communication KW - Speech KW - Telecommunication KW - Singing voice synthesizers KW - Pictorial data processing KW - Picture processing KW - Processing, Image KW - Imaging systems KW - Optical data processing KW - Processing, Signal KW - Information measurement KW - Signal theory (Telecommunication) UR - https://www.unicat.be/uniCat?func=search&query=sysid:14306199 AB - In this book, the authors provide insights into the basics of adaptive filtering, which are particularly useful for students taking their first steps into this field. They start by studying the problem of minimum mean-square-error filtering, i.e., Wiener filtering. Then, they analyze iterative methods for solving the optimization problem, e.g., the Method of Steepest Descent. By proposing stochastic approximations, several basic adaptive algorithms are derived, including Least Mean Squares (LMS), Normalized Least Mean Squares (NLMS) and Sign-error algorithms. The authors provide a general framework to study the stability and steady-state performance of these algorithms. The affine Projection Algorithm (APA) which provides faster convergence at the expense of computational complexity (although fast implementations can be used) is also presented. In addition, the Least Squares (LS) method and its recursive version (RLS), including fast implementations are discussed. The book closes with the discussion of several topics of interest in the adaptive filtering field. ER -