Radial Basis Function Networks 1: Recent Developments in Theory and Applications
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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.
Format:Hardcover
Language:English
ISBN:3790813672
ISBN13:9783790813678
Release Date:March 2001
Publisher:Physica-Verlag
Length:318 Pages
Weight:1.44 lbs.
Dimensions:0.8" x 6.1" x 9.2"
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