[comp.ai.neural-nets] Introductory Texts

bakker@batserver.cs.uq.oz.au (Paultje Bakker) (01/25/91)

(* Sorry for wasting bandwidth. Here's a cleaner version of the 
list I posted the other day. I'll post it every 2-3 months from
now on with updates. *)

A List of Introductory Texts for Neural Networks.

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- I haven't checked the accuracy of many of these titles. Beware!
- Wasserman's book is by far the most popular.
- Please send new additions or comments/corrections on existing 
items to bakker@batserver.cs.uq.oz.au. 
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Aleksander, I. and Morton, H. (1990). An Introduction to Neural Computing.
Chapman and Hall.

Anderson, J. A. and Rosenfeld, E. (1988). Neurocomputing: Foundations of 
Research. The MIT Press, Cambridge, MA.

Beale, R. and Jackson, T. (1990). Neural Computing, an Introduction.
Adam Hilger, IOP Publishing Ltd. (ISBN 0-85274-262-2).
Comments: "It's clearly written.  Lots of hints as to how to get the
adaptive models covered to work (not always well explained in the
original sources).  Consistent mathematical terminology.  Covers
perceptrons, error-backpropagation, Kohonen self-org model, Hopfield
type models, ART, and associative memories."

Caudill, M. and Butler, C. (1990). Naturally Intelligent Systems.
MIT Press: Cambridge, Massachusetts. (ISBN 0-262-03156-6)
Comments: "I guess one of the best books I read."

Hinton, G. E. (1989). Connectionist learning procedures.
Artificial Intelligence, Vol. 40, pp. 185--234.
Comments: "One of the better neural networks overview papers, although the
distinction between network topology and learning algorithm is not always
very clear.  Could very well be used as an introduction to neural networks."

Lippmann, R. P. (1987). An introduction to computing with neural nets.
IEEE Transactions on Acoustics, Speech, and Signal Processing. vol. 2,
no. 4, pp 4-22.
Comments: "Much acclaimed as an overview of neural networks, but rather 
inaccurate on several points.  The categorization into binary and continuous-
valued input neural networks is rather arbitrary, and may work confusing for
the unexperienced reader.  Not all networks discussed are of equal importance.

McClelland, J. L. and Rumelhart, D. E. (1988).
Explorations in Parallel Distributed Processing: Computational Models of 
Cognition and Perception (software manual). The MIT Press.
Comments: "Written in a tutorial style, and includes 2 diskettes of NN 
simulation programs that can be compiled on MS-DOS or Unix (and they do 
too !)"; "The programs are pretty reasonable as an introduction to some 
of the things that nns can do."

Pao, Y. H. (1989). Adaptive Pattern Recognition and Neural Networks
Addison-Wesley Publishing Company, Inc.(ISBN 0-201-12584-6)

[A paper by Rumelhart et.al published in Nature at the same time 
(vol 323 October 1986) gives a very good potted explanation of backprop NN's.
It gives sufficient detail to write your own NN simulation.]

Rumelhart, D. E. and McClelland, J. L. (1986). Parallel Distributed 
Processing: Explorations in the Microstructure of Cognition (volumes 1 & 2). 
The MIT Press. 
Comments:  "As a computer scientist I found the two Rumelhart and McClelland 
books really heavy going and definitely not the sort of thing to read if you 
are a beginner."; "It's quite readable, and affordable (about $65 for both 
volumes).";

Stanley, J. (1988,1989). Introduction to Neural Networks. California 
Scientific Software.
Comments: "This is provided with the Brainmaker nn package. It is however 
just what it claims to be; an introductory text. Perhaps a bit simplistic 
for some.."

Wasserman, P. D. (1989). Neural Computing: Theory & Practice
Van Nostrand Reinhold. (ISBN 0-442-20743-3)
Comments: Generally considered to be the best introductory text so far.

Wunsch, D. (Ed.) (July, 1991). Neural Networks: An Introduction.
Pergamon Press.

Zeidenberg. M. (1990). Neural Networks in Artificial Intelligence.
Ellis Horwood, Ltd., Chichester.

--
--Paul Bakker         email: bakker@batserver.cs.uq.oz.au
--Dept. of Scatology    "Love between the ugly
--University of Qld        Is the most beautiful love of all" 
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