Hardcover. Condition: Used - Very Good. Physica-Verlag, Heidelberg, copyright 2001. xix, 360 pages. Illustrated. 9.5 x 6.5", hardcover, no dj. No dj, clean, tight, very good/none.
Published by World Scientific Pub Co Inc, 1715
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Published by World Scientific Publishing Co Pte Ltd, 1999
ISBN 10: 9810237715 ISBN 13: 9789810237714
Language: English
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Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Heidelberg, 2001
ISBN 10: 3790813680 ISBN 13: 9783790813685
Language: English
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Hardcover. Condition: 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 2 contains a wide range of applications in the laboratory and case studies describing current industrial use. Both volumes will prove extremely useful to practitioners in the field, engineers, reserachers, students and technically accomplished managers. The Radial Basis Function (RBF) network has gained in popularity in recent years. The two-title series Theory and Applications of Radial Basis Function Networks provides a comprehensive survey of recent RBF network research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Heidelberg, 2011
ISBN 10: 3790824836 ISBN 13: 9783790824834
Language: English
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Paperback. Condition: new. Paperback. 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 2 contains a wide range of applications in the laboratory and case studies describing current industrial use. Both volumes will prove extremely useful to practitioners in the field, engineers, reserachers, students and technically accomplished managers. The Radial Basis Function (RBF) network has gained in popularity in recent years. The two-title series Theory and Applications of Radial Basis Function Networks provides a comprehensive survey of recent RBF network research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Heidelberg, 2010
ISBN 10: 3790824828 ISBN 13: 9783790824827
Language: English
Seller: Grand Eagle Retail, Mason, OH, U.S.A.
Paperback. Condition: new. Paperback. 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.
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Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
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