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Locating the centers in an RBF network

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Locating the centers in an RBF network

Content Provider	IEEE Xplore Digital Library
Author	Panchapakesan, C. Ralph, D. Palaniswami, M.
Copyright Year	1998
Description	Author affiliation: Melbourne Univ., Parkville, Vic., Australia (Panchapakesan, C.)
Abstract	In radial basis functions (RBF) networks both supervised and unsupervised methods are used to determine the location of centers. Though the supervised training of centers are reported to give longer training times it has been suggested that their generalising performance is better than the corresponding results when unsupervised methods are used in fixing the centers. A reduction in training time and better generalising ability dictates that we use the unsupervised methods to locate the centers and then fine tune them. Fine tuning them corresponds to finding a suitable step size to achieve a desired amount of reduction in the error. In this paper we have obtained bounds on the Hessian of the error function to get a suitable step size in the supervised training of the network.
Starting Page	234
Ending Page	237
File Size	312702
Page Count	4
File Format	PDF
ISBN	0780348869
DOI	10.1109/TENCON.1998.797129
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-12-17
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent networks Radial basis function networks Function approximation Supervised learning Mathematics Statistics Neural networks Pattern recognition Ear
Content Type	Text
Resource Type	Article

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