Digital Signal Processing Systems: Implementation Techniques, Volume 68: Advances in Theory and Applications PDF
Preview Digital Signal Processing Systems: Implementation Techniques, Volume 68: Advances in Theory and Applications
CONTROL AND DYNAMIC SYSTEMS Advances in Theory and Applications Volume 68 http://avaxhome.ws/blogs/ChrisRedfield CONTRIBUTORS TO THIS VOLUME ALBERTB ENVENIST E JAMES B. BURR D. HA TZINAK O S S IM ON HA YKIN CORNELIUS T. LEONDES WEIPING LI KEN MARTIN M UKUND PADMANABHAN ALLEN M. PETERSON PETER A. STUBBERUD MICHAIL K. TSATSANIS CONTROL AND DYNAMIC SYSTEMS ADVANCES IN THEORY AND APPLICATIONS Edited by C. T. LEONDES School of Engineering and Applied Science University of California, San Diego La Jolla, California VOLUME 68: DIGITAL SIGNAL PROCESSING SYSTEMS: IMPLEMENTATION TECHNIQUES ACADEMIC PRESS San Diego New York Boston London Sydney Tokyo Toronto This book is printed on acid-free paper. (~ Copyright (cid:14)9 1995 by ACADEMIC PRESS, INC. All Rights Reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Academic Press, Inc. A Division of Harcourt Brace & Company 525 B Street, Suite 1900, San Diego, California 92101-4495 United Kingdom Edition published by Academic Press Limited 24-28 Oval Road, London NW 1 7DX International Standard Serial Number: 0090-5267 International Standard Book Number: 0-12-012768-7 PRINTED IN THE UNITED STATES OF AMERICA 95 96 97 98 99 00 QW 9 8 7 6 5 4 3 2 1 CONTENTS CONTRIBUTORS ....................................... v i i PREFACE ............................................. i x VLSI Signal Processing ..................................... 1 James B. Burr, Weiping Li, and Allen M. Peterson Recurrent Neural Networks for Adaptive Filtering ................... 89 Simon Haykin Multiscale Signal Processing: From QMF to Wavelets ............... 121 Albert Benveniste The Design of Frequency Sampling Filters ....................... 163 Peter A. Stubberud and Cornelius T. Leondes Low-Complexity Filter-Banks for Adaptive and Other Applications ...... 197 Mukund Padmanabhan and Ken Martin A Discrete Time Nonrecursive Linear Phase Transport Processor Design Technique ............................................. 255 Peter A. Stubberud and Cornelius T. Leondes Blind Deconvolution: Channel Identification and Equalization ......... 279 D. Hatzinakos Time-Varying System Identification and Channel Equalization Using Wavelets and Higher-Order Statistics ........................... 333 Michail K. Tsatsanis INDEX ............................................... 395 This Page Intentionally Left Blank CONTRIBUTORS Numbers in parentheses indicate the pages on which the authors' contributions begin. Albert Benveniste (121), Institut de Recherche en Informatique et Systemes Ale- atoires, Campus Universitaire de Beaulieu, F-35042 Rennes, France James B. Burr (1), Electrical Engineering Department, Stanford University, Stanford, California 94305 D. Hatzinakos (279), Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada M5S 1A4 Simon Haykin (89), Communications Research Laboratory, McMaster Uni- versity, Hamilton, Ontario, Canada L8S 4K1 Cornelius T. Leondes (163, 255), School of Engineering, University of Calif- ornia, San Diego, La Jolla, California 92037 Weiping Li (1), Electrical Engineering and Computer Science Department, Lehigh University, Bethlehem, Pennsylvania 18015 Ken Martin (197), Electrical Engineering Department, University of Toronto, Toronto, Ontario, Canada M5S 1A4 Mukund Padmanabhan (197), IBM T. J. Watson Research Center, Yorktown Heights, New York 10598 Allen M. Peterson (1), Electrical Engineering Department, Stanford University, Stanford, California 94305 Peter A. Stubberud (163, 255), Department of Electrical and Computer En- gineering, University of Nevada, Las Vegas, Las Vegas, Nevada 89154 Michail K. Tsatsanis, (333), University of Virginia, Charlottesville, Virginia 22903 vii This Page Intentionally Left Blank PREFACE From about the mid-1950s to the early 1960s, the field of digital filtering, which was based on processing data from various sources on a mainframe com- puter, played a key role in the processing of telemetry data. During this time period the processing of airborne radar data was based on analog computer technology. In this application area, an airborne radar used in tactical aircraft could detect the radar return from another low-flying aircraft in the environment of competing radar return from the ground. This was accomplished by the pro- cessing and filtering of the radar signal by means of analog circuitry in order to take advantage of the Doppler frequency shift due to the velocity of the observed aircraft. This analog implementation was lacking in the flexibility and capability inherent in programmable digital signal processor technology, which was just coming onto the technological scene. Developments and powerful technological advances in integrated digital elec- tronics coalesced soon after the early 1960s to lay the foundations for modem digital signal processing. Continuing developments in techniques and support- ing technology, particularly very large scale integrated digital electronics cir- cuitry, have resulted in significant advances in many areas. These areas include consumer products, medical products, automotive systems, aerospace systems, geophysical systems, and defense-related systems. Hence, this is a particularly appropriate time for Control and Dynamic Systems to address the area of "Digital Signal Processing Systems: Implementation Techniques," the theme for this volume. The first contribution to this volume is "VLSI Signal Processing," by James B. Burr, Weiping Li, and Allen M. Peterson. This contribution gives an overview of digital implementations and techniques for high-performance digi- tal signal processing. The authors are to be most highly complimented for pro- ducing a self contained treatment with a high degree of clarity of this major and broad topic which underpins the implementation of digital signal processing systems. Needless to say, this is a most appropriate contribution with which to begin this volume. The next contribution is "Recurrent Neural Networks for Adaptive Filtering," by Simon Haykin. Adaptive filtering, which is an inherently nonlinear process, arises in such major application areas as identification, equalization (inverse modeling), prediction, and noise cancellation. This contribution presents rather powerfully effective neural network techniques which are ideally suited to adap-
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