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CRC.Press.COMPUTATIONAL.INTELLIGENCE.PARADIGMS.THEORY.AND.APPLICATIONS.USING.MATLAB
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Computational
Intelligence
Paradigms
Theory and
Applications
using MATLAB
®
© 2010 by Taylor and Francis Group, LLC
S. sumathi
surekha p.
Computational
Intelligence
Paradigms
Theory and
Applications
using MATLAB
®
A CHAPMAN & HALL BOOK
CRC Press is an imprint of the
Taylor & Francis Group, an informa business
Boca Raton London New York
© 2010 by Taylor and Francis Group, LLC
MATLAB ® and Simulink ® are trademarks of the Math Works, Inc. and are used with permission. The Mathworks does
not warrant the accuracy of the text or exercises in this book. This book’s use or discussion of MATLAB ® and Simulink
® software or related products does not constitute endorsement or sponsorship by the Math Works of a particular peda-
gogical approach or particular use of the MATLAB ® and Simulink ® software.
CRC Press
Taylor & Francis Group
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Boca Raton, FL 33487-2742
© 2010 by Taylor and Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business
No claim to original U.S. Government works
Printed in the United States of America on acid-free paper
10 9 8 7 6 5 4 3 2 1
International Standard Book Number: 978-1-4398-0902-0 (Hardback)
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Library of Congress Cataloging‑in‑Publication Data
Sumathi, S., 1968-
Computational intelligence paradigms : theory & applications using MATLAB / S. Sumathi and
Surekha Paneerselvam.
p. cm.
Includes bibliographical references and index.
ISBN 978-1-4398-0902-0 (hard back : alk. paper)
1. Computational intelligence. 2. MATLAB. I. Paneerselvam, Surekha, 1980- II. Title.
Q342.S94 2010
006.3--dc22 2009022113
Visit the Taylor & Francis Web site at
http://www.taylorandfrancis.com
and the CRC Press Web site at
http://www.crcpress.com
© 2010 by Taylor and Francis Group, LLC
Contents
Preface xvii
1 Computational Intelligence 1
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Primary Classes of Problems for CI Techniques . . . . 5
1.2.1 Optimization . . . . . . . . . . . . . . . . . . . 5
1.2.2 NP-Complete Problems . . . . . . . . . . . . . 6
1.3 Neural Networks . . . . . . . . . . . . . . . . . . . . . 7
1.3.1 Feed Forward Neural Networ ks . . . . . . . . . 8
1.4 Fuzzy Systems . . . . . . . . . . . . . . . . . . . . . . 9
1.4.1 Fuzzy Sets . . . . . . . . . . . . . . . . . . . . 9
1.4.2 Fuzzy Controllers . . . . . . . . . . . . . . . . 11
1.5 Evolutionary Computing . . . . . . . . . . . . . . . . . 12
1.5.1 Genetic Algorithms . . . . . . . . . . . . . . . 13
1.5.2 Genetic Programming . . . . . . . . . . . . . . 14
1.5.3 Evolutionary Programming . . . . . . . . . . . 15
1.5.4 Evolutionary Strategies . . . . . . . . . . . . . 15
1.6 Swarm Intelligence . . . . . . . . . . . . . . . . . . . . 16
1.7 Other Paradigms . . . . . . . . . . . . . . . . . . . . . 17
1.7.1 Granular Computing . . . . . . . . . . . . . . 18
1.7.2 Chaos Theory . . . . . . . . . . . . . . . . . . 20
1.7.3 Artificial Immune Systems . . . . . . . . . . . 21
1.8 Hybrid Approaches . . . . . . . . . . . . . . . . . . . . 22
1.9 Relationship with Other Paradigms . . . . . . . . . . . 23
1.10 Challenges To Computational Intelligence . . . . . . . 25
Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Review Questions . . . . . . . . . . . . . . . . . . . . . . . . 27
2 Artificial Neural Networks with MATLAB 29
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . 29
2.2 A B rief History of Neural Networks . . . . . . . . . . . 29
2.3 Artificial Neural Networks . . . . . . . . . . . . . . . . 32
2.3.1 Comparison of Neura l Network to the Brain . 33
2.3.2 Artificial Neurons . . . . . . . . . . . . . . . . 33
v
© 2010 by Taylor and Francis Group, LLC
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