Methods and Procedures for the Verification and Validation of Artificial Neural Networks - Brian J. Taylor.pdf

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Methods and Procedures for the
Verification and Validation of
Artificial Neural Networks
Methods and Procedures for the
Verification and Validation of
Artificial Neural Networks
edited by
Institute for Scientific Research, Inc.
Fairmont,WV, USA
Brian J. Taylor
13
Brian J. Taylor
Institute for Scientific Research, Inc.
320 Adams Street
Fairmont, WV 26555-2720
USA
btaylor@isr.us
Library of Congress Control Number: 2005933711
METHODS AND PROCEDURES FOR THE VERIFICATION AND
VALIDATION OF ARTIFICIAL NEURAL NETWORKS
Edited by Brian J. Taylor
Institute for Scientific Research, Inc.
ISBN-13: 978-0-387-28288-6
ISBN-10: 0-387-28288-2
e-ISBN-13: 978-0-387-29485-8
e-ISBN-10: 0-387-29485-6
Printed on acid-free paper.
2006 Springer Science+Business Media, Inc.
All rights reserved. This work may not be translated or copied in whole or
in part without the written permission of the publisher (Springer
Science+Business Media, Inc., 233 Spring Street, New York, NY 10013,
USA), except for brief excerpts in connection with reviews or scholarly
analysis. Use in connection with any form of information storage and
retrieval, electronic adaptation, computer software, or by similar or
dissimilar methodology now know or hereafter developed is forbidden.
The use in this publication of trade names, trademarks, service marks and
similar terms, even if the are not identified as such, is not to be taken as
an expression of opinion as to whether or not they are subject to
proprietary rights.
Printed in the United States of America.
9 8 7 6 5 4 3 2 1
springeronline.com
SPIN 11539124, 11570691
Contents
Contributing Authors
Preface
Acknowledgments
Background of the Verification and Validation of Neural Networks
Augmentation of Current Verification and Validation Practices
Risk and Hazard Analysis for Neural Network Systems
Validation of Neural Networks Via Taxonomic Evaluation
Stability Properties of Neural Networks
Neural Network Verification
Neural Network Visualization Techniques
Rule Extraction as a Formal Method
Automated Test Generation for Testing Neural Network Systems
Run-Time Assessment of Neural Network Control Systems
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