Path: utzoo!attcan!uunet!lll-winken!lll-tis!ames!ll-xn!oberon!pollux.usc.edu!pi
From: pi@pollux.usc.edu (Bill Pi)
Newsgroups: comp.ai.neural-nets
Subject: Re: Neural network information wanted
Summary: Neural network references, INNS Journal.
Message-ID: <10892@oberon.USC.EDU>
Date: 20 Jul 88 04:08:13 GMT
References: <220700001@uxe.cso.uiuc.edu> <348@macomw.ARPA> <14531@shemp.CS.UCLA.EDU>
Sender: news@oberon.USC.EDU
Reply-To: pi@pollux.usc.edu (Jen-I Pi)
Organization: University of Southern California, Los Angeles, CA
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In article <14531@shemp.CS.UCLA.EDU> kennel@minnie.cognet.ucla.edu (Matthew Kennel) writes:
>In article <348@macomw.ARPA> dtraver@macomw.UCSD.EDU (George Andrew Traver) writes:
>>In article <220700001@uxe.cso.uiuc.edu> richman@uxe.cso.uiuc.edu writes:
>>>
>>>Could someone recommend a good introductory text which deals with
>>>Neural Networks?  Please e-mail responses to:
>>
>>Me too!  Email to dtraver@macomw.arpa.
>
>There is no comprehensive introductory textbook that I've seen that
>deals with neural networks in anything more than a cursory treatment.
>
>The standard reference is Rumelhart and McClelland's two volume work
>"Parallel Distributed Processing.", published by the MIT press.

Volume 3 of the series is also available now from MIT Press:
"Explorations in Parallel Distributed Processing: A Handbook of Models,
 Programs, and Exercises", J. L. McClelland and D. E. Rumelhart, 1988.
It comes with two 5.25" floopy disks, which contain a set of seven simulation
problems describe in the book.

Also, you might want to check the official Journal of the International
Neural Network Society (INNS) called "Neural Networks" from Pergamon
Journals, Inc.

>
>The first few chapters are not particularly
>technical at all.  As a physics undergraduate, I found some of the
>references to psychology works somewhat obscure, but the basic concepts and
>mathematics were quite clear and simple.

For people with physic's background, you might want to check out the following
articles and their references:

1. "Spin-glass models of Neural Networks", D. J. Amit, H. Gutfreund, and H.
     Sompolinsky, Physical Review A, Vol. 32, No. 2, 1985, pp. 1007-1018.

2. "Spin Glass Model for a Neural Network: Associative Memories stored with
     Unequal Weights", J. Phys. France (or J. de Physique), Vol. 49, 1988,
     pp. 167-174.

Also, I find

3. "Bidirectional Associative Memories", B. Kosko, IEEE Trans. on Sys. Man
and Cybern., vol. 18, No. 1, 1988, pp.49-60.

also interesting.

Greetings,
Jen-I Pi :-)			     UUCP:    {sdcrdcf,cit-cav}!oberon!durga!pi
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