ISBN: 9788120325883

New Softcover NA Evolutionary computation is one of the new and fastest growing areas of computer science, particularly with regard to its application for solving difficult engineering pr… Mehr…

New Softcover NA Evolutionary computation is one of the new and fastest growing areas of computer science, particularly with regard to its application for solving difficult engineering problems from diverse disciplines. This concise, accessible introduction provides an overview of the basic principles and practice of evolutionary algorithms, with a focus on examples from the area of signal processing. The examples span a considerable range of applications and should be useful to a variety of readers with different backgrounds and expertise. Beginning with a survey of evolutionary computation, the book describes in detail the methodology of designing and optimizing mathematical models, and discusses how evolutionary algorithms can provide effective and potentially innovative means for addressing problems in clustering and classification-the two principal areas of research in signal processing. Evolutionary algorithms provide a variety of means for addressing optimal control problems. The examples presented in the book indicate a diverse set of applications of evolutionary algorithms for control. Finally, a relatively new approach to designing improved evolutionary algorithms that relies on fitness distribution of operators is described and its application to problems in signal processing and other domains is emphasized. Students of computer science and engineering would find this book extremely useful. Its lucid treatment provides the students with an opportunity to learn how evolutionary algorithms perform in practice. Contents Preface. 1. An Overview of Evolutionary Algorithms and Their Advantages. 2. Evolving Models of Time Series. 3. Evolutionary Clustering and Classification. 4. Evolving Control Systems. 5. Theory and Tools for Improving Evolutionary Algorithms. Index. Printed Pages: 184. First edition, [Evolutionary Computation: Principles and Practice for Signal ProcessingDavid B. Fogel9788120325883], PHI Learning 0000<

ISBN: 9788120325883

PHI Learning 0000, New Softcover . Evolutionary computation is one of the new and fastest growing areas of computer science, particularly with regard to its application for solving diffic… Mehr…

PHI Learning 0000, New Softcover . Evolutionary computation is one of the new and fastest growing areas of computer science, particularly with regard to its application for solving difficult engineering problems from diverse disciplines. This concise, accessible introduction provides an overview of the basic principles and practice of evolutionary algorithms, with a focus on examples from the area of signal processing. The examples span a considerable range of applications and should be useful to a variety of readers with different backgrounds and expertise. Beginning with a survey of evolutionary computation, the book describes in detail the methodology of designing and optimizing mathematical models, and discusses how evolutionary algorithms can provide effective and potentially innovative means for addressing problems in clustering and classification-the two principal areas of research in signal processing. Evolutionary algorithms provide a variety of means for addressing optimal control problems. The examples presented in the book indicate a diverse set of applications of evolutionary algorithms for control. Finally, a relatively new approach to designing improved evolutionary algorithms that relies on fitness distribution of operators is described and its application to problems in signal processing and other domains is emphasized. Students of computer science and engineering would find this book extremely useful. Its lucid treatment provides the students with an opportunity to learn how evolutionary algorithms perform in practice. Contents Preface. 1. An Overview of Evolutionary Algorithms and Their Advantages. 2. Evolving Models of Time Series. 3. Evolutionary Clustering and Classification. 4. Evolving Control Systems. 5. Theory and Tools for Improving Evolutionary Algorithms. Index. Printed Pages: 184. First edition, [Evolutionary Computation: Principles and Practice for Signal ProcessingDavid B. Fogel9788120325883]<