9780819437259-0819437255-Evolutionary Computation: Principles and Practice for Signal Processing (SPIE Tutorial Texts in Optical Engineering Vol. TT43)

Evolutionary Computation: Principles and Practice for Signal Processing (SPIE Tutorial Texts in Optical Engineering Vol. TT43)

ISBN-13: 9780819437259
ISBN-10: 0819437255
Author: David B. Fogel
Publication date: 2000
Publisher: SPIE Publications
Format: Paperback 184 pages
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Book details

ISBN-13: 9780819437259
ISBN-10: 0819437255
Author: David B. Fogel
Publication date: 2000
Publisher: SPIE Publications
Format: Paperback 184 pages

Summary

Evolutionary Computation: Principles and Practice for Signal Processing (SPIE Tutorial Texts in Optical Engineering Vol. TT43) (ISBN-13: 9780819437259 and ISBN-10: 0819437255), written by authors David B. Fogel, was published by SPIE Publications in 2000. With an overall rating of 4.0 stars, it's a notable title among other books. You can easily purchase or rent Evolutionary Computation: Principles and Practice for Signal Processing (SPIE Tutorial Texts in Optical Engineering Vol. TT43) (Paperback) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Evolutionary computation is one of the fastest growing areas of computer science, partly because of its broad applicability to engineering problems. The methods can be applied to problems as diverse as supply-chain optimization, routing and planning, task assignment, pharmaceutical design, interactive gaming, and many others within the signal processing domain. The book is an outgrowth of successful SPIE short courses taught by the author. The examples span a range of applications and should be useful to a variety of readers with different backgrounds and expertise.

Contents

- Preface
- An Overview of Evolutionary Algorithms and Their Advantages
- Evolving Models of Time Series
- Evolutionary Clustering and Classification
- Evolving Control Systems
- Theory and Tools for Improving Evolutionary Algorithms
- References
- Index

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