Overview

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.

Full Product Details

Author:   Robert J. Howlett ,  Lakhmi C. Jain
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Physica-Verlag GmbH & Co
Edition:   2001 ed.
Volume:   67
Dimensions:   Width: 15.50cm , Height: 2.20cm , Length: 23.50cm
Weight:   1.570kg
ISBN:  

9783790813685

ISBN 10:   3790813680
Pages:   360
Publication Date:   27 March 2001
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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