Radial Basis Function Networks
. Ed(s): Howlett, Robert J.; Jain, Prof. Lakhmi C.
ISBN 10: 3790813672 ISBN 13: 9783790813678
Verlag: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2001
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Providing a comprehensive survey of developments in the area of RBF networks, this volume 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. Editor(s): Howlett, Robert J.; Jain, Prof. Lakhmi C. Series: Studies in Fuzziness and Soft Computing. Num Pages: 318 pages, 14 black & white tables, biography. BIC Classification: UYQP. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 20. Weight in Grams: 653. . 2001. Hardback. . . . . Bestandsnummer des Verkäufers V9783790813678
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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.
Von der hinteren Coverseite: 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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Titel: Radial Basis Function Networks
Verlag: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Erscheinungsdatum: 2001
Einband: Hardcover
Zustand: New
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Radial Basis Function Networks 1 : Recent Developments in Theory and Applications
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Zustand: 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. Bestandsnummer des Verkäufers 5310329
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Radial Basis Function Networks 1: Recent Developments in Theory and Applications (Studies in Fuzziness and Soft Computing, 66)
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Physica-Verlag, Physica-Verlag HD, Physica Mrz 2001, 2001
ISBN 10: 3790813672
ISBN 13: 9783790813678
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Buch. Zustand: 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. Bestandsnummer des Verkäufers 9783790813678
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Buch. Zustand: 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 340 pp. Englisch. Bestandsnummer des Verkäufers 9783790813678
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Buch. Zustand: 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. Bestandsnummer des Verkäufers 9783790813678
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Radial Basis Function Networks 1 (Hardcover)
ISBN 10: 3790813672
ISBN 13: 9783790813678
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Hardcover. Zustand: new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9783790813678
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