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Radial Basis Function Networks 1: Recent Developments in Theory and Applications (Studies in Fuzziness and Soft Computing) - Softcover
Synopsis
The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of application areas, for example, robotics, biomedical engineering, and the financial sector. The two volumes provide a comprehensive survey of the latest developments in this area. Volume 1 covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms, for example RBF learning using genetic algorithms. Both volumes will prove extremely useful to practitioners in the field, engineers, researchers and technically accomplished managers.
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From the Back Cover
The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of application areas, for example, robotics, biomedical engineering, and the financial sector. The two volumes provide a comprehensive survey of the latest developments in this area. Volume 1 covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms, for example RBF learning using genetic algorithms. Both volumes will prove extremely useful to practitioners in the field, engineers, researchers and technically accomplished managers.
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- PublisherPhysica
- Publication date2010
- ISBN 10 3790824828
- ISBN 13 9783790824827
- BindingPaperback
- LanguageEnglish
- Number of pages336
- EditorJ.Howlett Robert, C. Jain Lakhmi
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of application areas, for example, robotics, biomedical engineering, and the financial sector. The two volumes provide a comprehensive survey of the latest developments in this area. Volume 1 covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms, for example RBF learning using genetic algorithms. Both volumes will prove extremely useful to practitioners in the field, engineers, researchers and technically accomplished managers. 318 pp. Englisch. Seller Inventory # 9783790824827
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Contains a wide range of applications in the laboratory and case-studies describing current use Overall view of the methods used for the genetic optimisation of artificial neural networks and presentation of the inherent problemsThe Radial Basis Fun. Seller Inventory # 5310748
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of application areas, for example, robotics, biomedical engineering, and the financial sector. The two volumes provide a comprehensive survey of the latest developments in this area. Volume 1 covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms, for example RBF learning using genetic algorithms. Both volumes will prove extremely useful to practitioners in the field, engineers, researchers and technically accomplished managers. Seller Inventory # 9783790824827
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Taschenbuch. Condition: Neu. Neuware -The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of application areas, for example, robotics, biomedical engineering, and the financial sector. The two volumes provide a comprehensive survey of the latest developments in this area. Volume 1 covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms, for example RBF learning using genetic algorithms. Both volumes will prove extremely useful to practitioners in the field, engineers, researchers and technically accomplished managers.Physica Verlag, Tiergartenstr. 17, 69121 Heidelberg 336 pp. Englisch. Seller Inventory # 9783790824827
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