Principles of Adaptive Filters and Self-learning Systems
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 intro
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Series Editors Professor Michael J. Grimble, Professor of Industrial Systems and Director Professor Emeritus Michael A. Johnson, Professor of Control Systems and Deputy Director Industrial Control Centre, Department of Electronic and Electrical Engineering, University of Strathclyde, Graham Hills Building, 50 George Street, Glasgow G1 1QE, U.K.
Other titles published in this series: Genetic Algorithms K.F. Man, K.S. Tang and S. Kwong Neural Networks for Modelling and Control of Dynamic Systems M. Nørgaard, O. Ravn, L.K. Hansen and N.K. Poulsen Modelling and Control of Robot Manipulators (2nd Edition) L. Sciavicco and B. Siciliano Fault Detection and Diagnosis in Industrial Systems L.H. Chiang, E.L. Russell and R.D. Braatz Soft Computing L. Fortuna, G. Rizzotto, M. Lavorgna, G. Nunnari, M.G. Xibilia and R. Caponetto Statistical Signal Processing T. Chonavel Discrete-time Stochastic Processes (2nd Edition) T. Söderström Parallel Computing for Real-time Signal Processing and Control M.O. Tokhi, M.A. Hossain and M.H. Shaheed Multivariable Control Systems P. Albertos and A. Sala Control Systems with Input and Output Constraints A.H. Glattfelder and W. Schaufelberger Analysis and Control of Non-linear Process Systems K. Hangos, J. Bokor and G. Szederkényi Model Predictive Control (2nd Edition) E.F. Camacho and C. Bordons Digital Self-tuning Controllers V. Bobál, J. Böhm, J. Fessl and J. Macháˇcek Control of Robot Manipulators in Joint Space R. Kelly, V. Santibáñez and A. Loría Publication due July 2005 Robust Control Design with MATLAB® D.-W. Gu, P.Hr. Petkov and M.M. Konstantinov Publication due July 2005 Active Noise and Vibration Control M.O. Tokhi Publication due November 2005
A. Zaknich
Principles of Adaptive Filters and Self-learning Systems With 95 Figures
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Anthony Zaknich, PhD School of Engineering Science, Rockingham Campus, Murdoch University, South Street, Murdoch, WA 6150, Australia and Centre for Intelligent Information Processing Systems, School of Electrical, Electronic and Computer Engineering, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia Instructors Solutions Manual in PDF can be downloaded from the book’s page at springeronline.com
British Library Cataloguing in Publication Data Zaknich, Anthony Principles of adaptive filters and self-learning systems. (Advanced textbooks in control and signal processing) 1. Adaptive filters 2. Adaptive signal processing 3. System analysis I. Title 621.3’815324 ISBN-10: 1852339845 Library of Congress Control Number: 2005923608 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be
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