Description: Principles of Adaptive Filters and Self-learning Systems by Anthony Zaknich The topics of control engineering and signal processing continue to flourish and develop. A new concept in control and signal processing is known to have arrived when sufficient material has evolved for the topic to be taught as a specialised tutorial workshop or as a course to undergraduate, graduate or industrial engineers. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description This is an ideal textbook for one-semester introductory graduate or senior undergraduate courses in adaptive and self-learning systems for signal processing. The material progresses from a short introduction to adaptive systems through modelling, classical filters and spectral analysis to adaptive control theory, nonclassical adaptive systems and applications.Features:- Comprehensive review of linear and stochastic theory.- Design guide for practical application of the least squares estimation method and Kalman filters.- Study of classical adaptive systems together with neural networks, genetic algorithms and fuzzy logic systems and their combination deals with complex problems like underwater acoustic signal processing.- Tutorial problems and exercises which identify significant points and demonstrate the practical relevance of the theory.- PDF Solutions Manual available to tutors containing answers to the tutorial problems, course outlines, sample examination material and project assignments. Notes How can a signal be processed for which there are few or no a priori data? Professor Zaknich provides an ideal textbook for one-semester introductory graduate or senior undergraduate courses in adaptive and self-learning systems for signal processing applications. Important topics are introduced and discussed sufficiently to give the reader adequate background for confident further investigation. The material is presented in a progression from a short introduction to adaptive systems through modelling, classical filters and spectral analysis to adaptive control theory, nonclassical adaptive systems and applications. This is the first text to cover Kalman and Wiener filters, neural networks, genetic algorithms and fuzzy logic systems together in a unified treatment. Back Cover Kalman and Wiener Filters, Neural Networks, Genetic Algorithms and Fuzzy Logic Systems Together in One Text Book How can a signal be processed for which there are few or no a priori data? Professor Zaknich provides an ideal textbook for one-semester introductory graduate or senior undergraduate courses in adaptive and self-learning systems for signal processing applications. Important topics are introduced and discussed sufficiently to give the reader adequate background for confident further investigation. The material is presented in a progression from a short introduction to adaptive systems through modelling, classical filters and spectral analysis to adaptive control theory, nonclassical adaptive systems and applications. Features: * Comprehensive review of linear and stochastic theory. * Design guide for practical application of the least squares estimation method and Kalman filters. * Study of classical adaptive systems together with neural networks, genetic algorithms and fuzzy logic systems and their combination to deal with such complex problems as underwater acoustic signal processing. * Tutorial problems and exercises which identify the significant points and demonstrate the practical relevance of the theory. * PDF Solutions Manual, available to tutors from springeronline.com, containing not just answers to the tutorial problems but also course outlines, sample examination material and project assignments to help in developing a teaching programme and to give ideas for practical investigations. Author Biography Anthony Zaknich (M87-00) was born in Vela Luka, Croatia, and immigrated to Australia in the 1950s. He received the B.E. (Electronics) and M.E.Sc. degrees from the University of Western Australia (UWA), Nedlands in 1974 and 1986, respectively; the B.A. and B.Sc. (Psychology) degrees from Ambassador University, Pasadena, CA, USA, both in 1978; and the Ph.D. degree from UWA in 1996. He is currently an Adjunct Associate Professor at UWA, Centre for Intelligent Information Processing Systems (CIIPS) and also at Murdoch University, Perth Western Australia (Division of Science and Engineering). From 1990 to 1999 he held the position of Technical Manager for Industry Projects working as a Research Fellow and Lecturer at CIIPS in the Electrical and Electronics Engineering Department, UWA. His main work at CIIPS was involved with supervision, teaching, research and development related to signal processing and artificial neural networks at the undergraduate, postgraduate and professional-development levels. Previously, he was involved in the research and development of underwater control and acoustic signalling systems in private enterprise, and also in the establishment of a public company, Nautronix Ltd, producing and marketing products in these areas for the international market. He has supervised numerous Honours and ten postgraduate research projects, including three Ph.Ds. He has also authored/co-authored more than 56 refereed papers in technical journals and conference proceedings, has contributed five research book chapters, and authored two books in his areas of interest since 1988. His special research interest is related to integrated sensory-intelligent systems (ISIS): The philosophy, theory and applications of, intelligent signal processing; learning theory; self-learning systems; artificial neural networks; adaptive systems; time-frequency filters and signal analysis; time delay spectrometry; adaptive space-time-frequency signal processing; audio and Hi-Fi, and underwater acoustic communications systems. Dr Zaknich is a Member of the Audio Engineering Society (AES). He served on the IEEE Western Australian Regional Interest Group Committee on Neural Networks at various times since 1993. In 1998 he won the 1996-98, UWA Electrical and Electronics Engineering Departments Outstanding Early Researcher Award, which is given to the best researcher below Senior Lecturer level over any three year period. Table of Contents Adaptive Filtering.- Linear Systems and Stochastic Processes.- Modelling.- Optimisation and Least Squares Estimation.- Parametric Signal and System Modelling.- Classical Filters and Spectral Analysis.- Optimum Wiener Filter.- Optimum Kalman Filter.- Power Spectral Density Analysis.- Adaptive Filter Theory.- Adaptive Finite Impulse Response Filters.- Frequency Domain Adaptive Filters.- Adaptive Volterra Filters.- Adaptive Control Systems.- Nonclassical Adaptive Systems.- to Neural Networks.- to Fuzzy Logic Systems.- to Genetic Algorithms.- Adaptive Filter Application.- Applications of Adaptive Signal Processing.- Generic Adaptive Filter Structures. Review From the reviews:"An excellent tutorial for graduate students and a comprehensive introduction for researchers working in adaptive systems. Summing Up: Highly Recommended."(J. Y. Cheung, Choice, February, 2006) Long Description The topics of control engineering and signal processing continue to flourish and develop. In common with general scientific investigation, new ideas, concepts and interpretations emerge quite spontaneously and these are then discussed, used, discarded or subsumed into the prevailing subject paradigm. Sometimes these innovative concepts coalesce into a new sub-discipline within the broad subject tapestry of control and signal processing. This preliminary battle between old and new usually takes place at conferences, through the Internet and in the journals of the discipline. After a little more maturity has been acquired by the new concepts then archival publication as a scientific or engineering monograph may occur. A new concept in control and signal processing is known to have arrived when sufficient material has evolved for the topic to be taught as a specialised tutorial workshop or as a course to undergraduate, graduate or industrial engineers. Advanced Textbooks in Control and Signal Processing are designed as a vehicle for the systematic presentation of course material for both popular and innovative topics in the discipline. It is hoped that prospective authors will welcome the opportunity to publish a structured and systematic presentation of some of the newer emerging control and signal processing technologies in the textbook series. Review Quote From the reviews:"An excellent tutorial for graduate students and a comprehensive introduction for Feature Teaches students about classical and nonclassical adaptive systems within one pair of covers Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful technology for solving complex nonlinear problems Description for Sales People How can a signal be processed for which there are few or no a priori data? Professor Zaknich provides an ideal textbook for one-semester introductory graduate or senior undergraduate courses in adaptive and self-learning systems for signal processing applications. Important topics are introduced and discussed sufficiently to give the reader adequate background for confident further investigation. The material is presented in a progression from a short introduction to adaptive systems through modelling, classical filters and spectral analysis to adaptive control theory, nonclassical adaptive systems and applications. This is the first text to cover Kalman and Wiener filters, neural networks, genetic algorithms and fuzzy logic systems together in a unified treatment. Details ISBN1852339845 Author Anthony Zaknich Short Title PRINCIPLES OF ADAPTIVE FILTERS Pages 386 Language English ISBN-10 1852339845 ISBN-13 9781852339845 Media Book Year 2005 Imprint Springer London Ltd Place of Publication England Country of Publication United Kingdom Format Paperback Subtitle With 95 Figures DOI 10.1007/b94990;10.1007/b138890 AU Release Date 2005-04-25 NZ Release Date 2005-04-25 UK Release Date 2005-04-25 Publisher Springer London Ltd Edition Description 2005 ed. Series Advanced Textbooks in Control and Signal Processing Edition 2005th Publication Date 2005-04-25 DEWEY 519 Audience General Illustrations 95 Illustrations, black and white; XXII, 386 p. 95 illus. We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:96233241;
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ISBN-13: 9781852339845
Book Title: Principles of Adaptive Filters and Self-learning Systems
Number of Pages: 386 Pages
Language: English
Publication Name: Principles of Adaptive Filters and Self-Learning Systems
Publisher: Springer London Ltd
Publication Year: 2005
Subject: Engineering & Technology, Computer Science
Item Height: 235 mm
Item Weight: 1260 g
Type: Textbook
Author: Anthony Zaknich
Subject Area: Material Science, Mechanical Engineering, Electrical Engineering
Item Width: 155 mm
Format: Paperback