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
