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Recurrent Neural Networks for Prediction
Authored by Danilo P. Mandic, Jonathon A. Chambers
Copyright
c
2001 John Wiley & Sons Ltd
ISBNs: 0-471-49517-4 (Hardback); 0-470-84535-X (Electronic)
RECURRENT
NEURAL
NETWORKS
FOR PREDICTION
WILEY SERIES IN ADAPTIVE AND LEARNING SYSTEMS FOR
SIGNAL PROCESSING, COMMUNICATIONS, AND CONTROL
Editor: Simon Haykin
Beckerman/ADAPTIVE COOPERATIVE SYSTEMS
Chen and Gu/CONTROL-ORIENTED SYSTEM IDENTIFICATION: An H
Approach
Cherkassky and Mulier/LEARNING FROM DATA: Concepts, Theory and Methods
Diamantaras and Kung/PRINCIPAL COMPONENT NEURAL NETWORKS:
Theory and Applications
Haykin and Puthusserypady/CHAOTIC DYNAMICS OF SEA CLUTTER
Haykin/NONLINEAR DYNAMICAL SYSTEMS: Feedforward Neural Network
Perspectives
Haykin/UNSUPERVISED ADAPTIVE FILTERING, VOLUME I: Blind Source
Separation
Haykin/UNSUPERVISED ADAPTIVE FILTERING, VOLUME II: Blind
Deconvolution
Hines/FUZZY AND NEURAL APPROACHES IN ENGINEERING
Hrycej/NEUROCONTROL: Towards an Industrial Control Methodology
Krstic, Kanellakopoulos, and Kokotovic/NONLINEAR AND ADAPTIVE
CONTROL DESIGN
Mann/INTELLIGENT IMAGE PROCESSING
Nikias and Shao/SIGNAL PROCESSING WITH ALPHA-STABLE
DISTRIBUTIONS AND APPLICATIONS
Passino and Burgess/STABILITY ANALYSIS OF DISCRETE EVENT SYSTEMS
Sanchez-Pe˜na and Sznaier/ROBUST SYSTEMS THEORY AND APPLICATIONS
Tao and Kokotovic/ADAPTIVE CONTROL OF SYSTEMS WITH ACTUATOR
AND SENSOR NONLINEARITIES
Van Hulle/FAITHFUL REPRESENTATIONS AND TOPOGRAPHIC MAPS:
From Distortion- to Information-Based Self-Organization
Vapnik/STATISTICAL LEARNING THEORY
Werbos/THE ROOTS OF BACKPROPAGATION: From Ordered Derivatives to
Neural Networks and Political Forecasting
Yee and Haykin/REGULARIZED RADIAL-BASIS FUNCTION NETWORKS:
Theory and Applications
RECURRENT
NEURAL
NETWORKS
FOR PREDICTION
LEARNING ALGORITHMS,
ARCHITECTURES AND STABILITY
Danilo P. Mandic
School of Information Systems,
University of East Anglia, UK
Jonathon A. Chambers
Department of Electronic and Electrical Engineering,
University of Bath, UK
JOHN WILEY & SONS, LTD
Chichester
•
New York
•
Weinheim
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Brisbane
•
Singapore
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Copyright
c
2001 John Wiley & Sons, Ltd
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International (+44) 1243 779777
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All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval
system, or transmitted, in any form or by any means, electronic, mechanical, photocopying,
recording, scanning or otherwise, except under the terms of the Copyright Designs and
Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency
Ltd, 90 Tottenham Court Road, London, W1P 0LP, UK, without the permission in writing
of the Publisher, with the exception of any material supplied specifically for the purpose
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Neither the author(s) nor John Wiley & Sons Ltd accept any responsibility or liability for
loss or damage occasioned to any person or property through using the material, instruc-
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Library of Congress Cataloging-in-Publication Data
Mandic, Danilo P.
Recurrent neural networks for prediction : learning algorithms, architectures, and
stability / Danilo P. Mandic, Jonathon A. Chambers.
p. cm - - (Wiley series in adaptive and learning systems for signal processing,
communications, and control)
Includes bibliographical references and index.
ISBN 0-471-49517-4 (alk. paper)
1. Machine learning. 2. Neural networks (Computer science) I. Chambers, Jonathon A.
II. Title. III. Adaptive and learning systems for signal processing, communications, and
control.
Q325.5 .M36 2001
006.3
2- -dc21 2001033418
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
ISBN 0-471-49517-4
Produced from L
A
T
E
X files supplied by the author, typeset by T
&
T Productions Ltd, London.
Printed and bound in Great Britain by Antony Rowe, Chippenham, Wiltshire.
This book is printed on acid-free paper responsibly manufactured from sustainable forestry, in
which at least two trees are planted for each one used for paper production.
To our students and families
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