Radial Basis Function Networks 2 - New Advances in Design (Hardcover, 2001 ed.)

The Radial Basis Function (RBF) network has gained in popularity in recent years. This is due to its desirable properties in classification and functional approximation applications, accompanied by training that is more rapid than that of many other neural-network techniques. 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 applications areas, for example, robotics, biomedical engineering, and the financial sector. The two-title series Theory and Applications of Radial Basis Function Networks provides a comprehensive survey of recent RBF network research. This volume, New Advances in Design, contains a wide range of applications in the laboratory and case-studies describing current use. The sister volume to this one, Recent Developments in Theory and Applications, covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms. The combination of the two volumes will prove extremely useful to practitioners in the field, engineers, researchers, students and technically accomplished managers.

General

Imprint:	Physica-Verlag
Country of origin:	Germany
Series:	Studies in Fuzziness and Soft Computing, 67
Release date:	2001
First published:	2001
Authors:	Robert J. Howlett • Lakhmi C. Jain
Dimensions:	235 x 155 x 22mm (L x W x T)
Format:	Hardcover
Pages:	360
Edition:	2001 ed.
ISBN-13:	978-3-7908-1368-5
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition
LSN:	3-7908-1368-0
Barcode:	9783790813685

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