Fast and Efficient Training of RBF Networks-Reference-Cited by-同舟云学术

Fast and Efficient Training of RBF Networks

Published:2003 Issue: Volume: Page:43-51
ISSN:0302-9743
Container-title:Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003
language:
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Author:

Buchtala Oliver,Hofmann Alexander,Sick Bernhard

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-44989-2_6

Reference26 articles.

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3. Poggio, T., Girosi, F.: A theory of networks for approximation and learning. A.I. Memo No. 1140, C.B.I.P. Paper No. 31, Mass. Inst. of Tech. — Artif. Intell. Lab. & Center for Biol. Information Processing — Whitaker College (1989)

4. Jin, Y., von Seelen, W., Sendhoff, B.: Extracting interpretable fuzzy rules from RBF neural networks. Int. Rep. 2000–02, Institut für Neuroinformatik (INF), Ruhr-Universität Bochum (2000)

5. Moody, J., Darken, C.J.: Fast learning in networks of locally-tuned processing units. In: Neural Computation. Vol. 1. (1989) 281–294

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