richman@uxe.cso.uiuc.edu (07/15/88)
Could someone recommend a good introductory text which deals with
Neural Networks? Please e-mail responses to:
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Mike Richman
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Thanks!dtraver@macomw.ARPA (George Andrew Traver) (07/19/88)
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. Thanks in advance. ******************************************************************************* Success has many fathers :-), while failure is an orphan. :-( ------------------------------------------------------------------------------ The views expressed in this article are shared by no other living being or organization I know of. ( especialy my girlfreind ) dtraver@macomw.arpa FLAMES > /dev/null *******************************************************************************
kennel@minnie.cognet.ucla.edu (Matthew Kennel) (07/19/88)
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. 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. Matt K. (kennel@cognet.ucla.edu)
sbrunnoc@hawk.ulowell.edu (Sean Brunnock) (07/20/88)
From article <14531@shemp.CS.UCLA.EDU>, by kennel@minnie.cognet.ucla.edu (Matthew Kennel): >>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: > > The standard reference is Rumelhart and McClelland's two volume work > "Parallel Distributed Processing.", published by the MIT press. I find the textbook "Explorations in Parallel Distributed Processing" by the same authors to be a better book. It is more concise and contains C source code for the IBM-PC. Sean Brunnock
pi@pollux.usc.edu (Bill Pi) (07/20/88)
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 Department of Electrical Engineering CSnet: pi@usc-cse.csnet University of Southern California Bitnet: pi@uscvaxq Los Angeles, Ca. 90089-0781 InterNet: pi%durga.usc.edu@oberon.USC.EDU
tyler@boulder.Colorado.EDU (Tyler Stevens) (07/28/88)
>There is no comprehensive introductory textbook that I've seen that >deals with neural networks in anything more than a cursory treatment. >Matt K. >(kennel@cognet.ucla.edu) I took a class with Paul Smolensky (of PDP-group fame), here at CU-Boulder - and I believe he is currently working on an introductory text to PDP, etc. (We used several chapters of it; it is very good.) Keep your eyes pealed to this space, and I'll post the name of it when it comes out sometime in the indefinite future. tyler tyler@boulder.colorado.edu
demers@beowulf.ucsd.edu (David E Demers) (07/28/88)
Robert Hecht-Nielsen is writing a textbook on Neurocomputing. It is applications oriented; however, it outlines the history of the models used and the field itself. It also delves into the mathematics of neural nets quite heavily, including problems to avoid in converting data into an appropriate format for input to a net. It will be published by Addison-Wesley, due date is late 88. It will be the text from which he teaches his year-long course at UCSD. Dave DeMers demers@cs.ucsd.edu UCSD C-014 La Jolla, CA