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From: awillia@woodlawn.uchicago.edu (alan williams)
Subject: Re: What good overviews of NNs are available
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Date: Mon, 7 Aug 1995 23:16:57 GMT
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In article <3vqtho$eb6@news.cais.com>,  <RGOULD@imagi.net> wrote:
     
>What good overviews are there for neural nets?  I have a background in
>statistics and am interested in something which covers the field, as
>well as the most popular training methodologies.  Any assistance would
>be appreciated.
     

I'd recommend "Neural Networks: a comprehensive introduction", by Simon
Haykin (1994). Written from an engineering perspective, but gives much
mathematical detail and is (as claimed) admirably comprehensive. (It's
about 650 pages.) Haykin is a well-known author of engineering textbooks,
so his pedagogical skills are pretty good. 
   
The book by Hertz, Krogh, and Palmer (mentioned in previous post) is
also excellent, concentrating on pure theory rather than applications,
using methods inspired primarily by statistical physics. 
   
These two books, alas, are far and away the best ones I've found for
pure neural network stuff; most volumes at present are either compilations
of research papers (not very useful for a beginner) or just plain lousy
textbooks.  :-(   Hopefully this sad state of affairs is due solely to
the youth of the field, and will eventually improve. 
   
If you're at all interested in biological applications of neural modelling,
I can't resist recommending Churchland & Sejnowski's "The Computational
Brain" (1992) - a superb introduction.  :-)
   
    -- alan williams
  



