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From: saswss@hotellng.unx.sas.com (Warren Sarle)
Subject: Re: Intro to RBF
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Date: Fri, 5 Jul 1996 00:42:01 GMT
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In article <51afxhxpz3.fsf@kal-el.ugr.es>, jmerelo@kal-el.ugr.es (J.J. Merelo Guervos) writes:
|>      Is there any online material that explains clearly how RBF
|> networks learn, how many classes are there and so on? Is there a good
|> offline article I can consult? The FAQ gives reference to a book,
|> Bishop, but no article or online material.

Perhaps you were looking at an old copy of the FAQ. The current version
at ftp://ftp.sas.com/pub/neural/FAQ2.html includes several articles,
including Orr's on-line introductory article:

   Chen, S., Cowan, C.F.N., and Grant, P.M. (1991), "Orthogonal
   least squares learning for radial basis function networks,"
   IEEE Transactions on Neural Networks, 2, 302-309.

   Orr, M.J.L. (1995), "Regularisation in the selection of radial
   basis function centres," Neural Computation, 7, 606-623.

   Orr, M.J.L. (199?), "Introduction to radial basis function
   networks," http://www.cns.ed.ac.uk/people/mark/intro.ps or
   http://www.cns.ed.ac.uk/people/mark/intro/intro.html .

   Tao, K.M. (1993), "A closer look at the radial basis function (RBF)
   networks," Conference Record of The Twenty-Seventh Asilomar 
   Conference on Signals, Systems and Computers (Singh, A., ed.),
   vol 1, 401-405, Los Alamitos, CA: IEEE Comput. Soc. Press.

   Tarassenko, L. and Roberts, S. (1994), "Supervised and unsupervised
   learning in radial basis function classifiers," IEE Proceedings--
   Vis. Image Signal Processing, 141, 210-216.

   Werntges, H.W. (1993), "Partitions of unity improve neural
   function approximation," Proceedings of the IEEE International
   Conference on Neural Networks, San Francisco, CA, vol 2, 914-918.


-- 

Warren S. Sarle       SAS Institute Inc.   The opinions expressed here
saswss@unx.sas.com    SAS Campus Drive     are mine and not necessarily
(919) 677-8000        Cary, NC 27513, USA  those of SAS Institute.
