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Genetic Algorithms for Control and Signal Processing

  • Kim F. Man
  • Kit S. Tang
  • Sam Kwong
  • Wolfgang A. Halang

Part of the Advances in Industrial Control book series (AIC)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Kim F. Man, Kit S. Tang, Sam Kwong, Wolfgang A. Halang
    Pages 1-20
  3. Kim F. Man, Kit S. Tang, Sam Kwong, Wolfgang A. Halang
    Pages 21-29
  4. Kim F. Man, Kit S. Tang, Sam Kwong, Wolfgang A. Halang
    Pages 31-48
  5. Kim F. Man, Kit S. Tang, Sam Kwong, Wolfgang A. Halang
    Pages 49-112
  6. Kim F. Man, Kit S. Tang, Sam Kwong, Wolfgang A. Halang
    Pages 113-122
  7. Kim F. Man, Kit S. Tang, Sam Kwong, Wolfgang A. Halang
    Pages 123-148
  8. Kim F. Man, Kit S. Tang, Sam Kwong, Wolfgang A. Halang
    Pages 149-186
  9. Back Matter
    Pages 187-211

About this book

Introduction

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies, . . . , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The emerging technologies in control include fuzzy logic, intelligent control, neural networks and hardware developments like micro-electro-mechanical systems and autonomous vehicles. This volume describes the biological background, basic construction and application of the emerging technology of Genetic Algorithms. Dr Kim Man and his colleagues have written a book which is both a primer introducing the basic concepts and a research text which describes some of the more advanced applications of the genetic algorithmic method. The applications described are especially useful since they indicate the power of the GA method in solving a wide range of problems. These sections are also instructive in showing how the mechanics of the GA solutions are obtained thereby acting as a template for similar types of problems. The volume is a very welcome contribution to the Advances in Industrial Control Series. M. J. Grimble and M. A.

Keywords

algorithm control filter design neural networks optimization signal processing

Authors and affiliations

  • Kim F. Man
    • 1
  • Kit S. Tang
    • 1
  • Sam Kwong
    • 2
  • Wolfgang A. Halang
    • 3
  1. 1.Electrical Engineering DepartmentCity University of Hong KongKowloonHong Kong
  2. 2.Computer Science DepartmentCity University of Hong KongKowloonHong Kong
  3. 3.Faculty of Electrical EngineeringFern UniversitatHagenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-0955-6
  • Copyright Information Springer-Verlag London 1997
  • Publisher Name Springer, London
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4471-1241-9
  • Online ISBN 978-1-4471-0955-6
  • Series Print ISSN 1430-9491
  • Series Online ISSN 2193-1577
  • Buy this book on publisher's site