bakker@cs.uq.oz.au (Paultje Bakker) (04/05/91)
(Last posted : 15/1/91)
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 and Hertz et al seem to be the most popular.
- Please send new additions or comments/corrections on existing
items to bakker@cs.uq.oz.au.
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Aleksander, I. and Morton, H. (1990). An Introduction to Neural Computing.
Chapman and Hall. (ISBN 0-412-37780-2).
Anderson, J. A. and Rosenfeld, E. (1988). Neurocomputing: Foundations of
Research. The MIT Press: Cambridge, MA.
Comments: "An expensive book, but excellent for reference. It is a collection
of reprints of most of the major papers in the field."
Beale, R. and Jackson, T. (1990). Neural Computing, an Introduction.
Adam Hilger, IOP Publishing Ltd : Bristol. (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."
Butler, C.T. and Caudill, M. (199?). Introduction to neural networks.
Lawrence Erlbaum: East Sussex.
Comments: "Our library has this on order. I haven't seen it yet."
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"; "May not be suited for
people who want to do some research in the area".
Dayhoff, J. E. (1990). Neural Network Architectures: An Introduction.
Van Nostrand Reinhold: New York.
Comments: "Like Wasserman's book, Dayhoff's book is also very easy to
understand".
Eberhart, R. C. and Dobbins, R. W. (Eds). (1990). Neural Network PC Tools: A
Practical Guide. Academic Press: New York. (ISBN 0-12-228640-5).
Freeman, J., and Skapura, D. (1991). Artificial Neural Systems: Theory and
Practice. The Academic Press: New York.
Hecht-Nielsen, R. (1990). Neurocomputing. Addison Wesley.
Comments: "A good book".
Hertz, J., Krogh, A., and Palmer, R. (1991). Introduction to the Theory of
Neural Computation. Addison-Wesley: Redwood City, California.
Comments: "My first impression is that this one is by far the best book on
the topic. And it's below $30 for the paperback."; "Well wriiten, theoretical
(but not overwhelming)"; It provides a good balance of model development,
computational algorithms, and applications. The mathematical derivations
are especially well done"; "Nice mathematical analysis on the mechanism of
different learning algorithms".
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."
Khanna, T. (1990). Foundations of Neural Networks. Addison-Wesley: New York.
Comments: "Not so bad (with a page of erroneous formulas (if I remember
well), and #hidden layers isn't well described)."; "Khanna's intention
in writing his book with math analysis should be commended but he
made several mistakes in the math part".
Knight, K. (1990). Connectionist, Ideas and Algorithms. Communications of
the ACM. November 1990. Vol.33 nr.11, pp 59-74.
Comments:"A good article, while it is for most people easy to find a copy of
this journal."
Kohonen, T. (1984). Self-organization and Associative Memory. Springer-Verlag:
New York. (2nd Edition: 1988; 3rd edition: 1989).
Comments: "The section on Pattern mathematics is excellent."
Kohonen, T. (1988). An Introduction to Neural Computing. Neural Networks,
vol. 1, no. 1. pp. 3-16.
Comments: "A general review".
Levine, D. S. (1990). Introduction to Neural and Cognitive Modeling.
Lawrence Erlbaum: Hillsdale, N.J.
Comments: "Highly recommended".
Lippmann, R. P. (April 1987). An introduction to computing with neural nets.
IEEE Acoustics, Speech, and Signal Processing Magazine. 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."; "There are *two* editions of this book.
One comes with disks for the IBM PC, the other comes with disks for the
Macintosh".
McCord Nelson, M. and Illingworth, W.T. (1990). A Practical Guide to Neural
Nets. Addison-Wesley Publishing Company, Inc. (ISBN 0-201-52376-0).
Comments: "No formulas at all( ==> no good)"; "It does not have much
detailed model development (very few equations), but it does present many
areas of application. It includes a chapter on current areas of research.
A variety of commercial applications is discussed in chapter 1. It also
includes a program diskette with a fancy graphical interface (unlike the
PDP diskette)".
Pao, Y. H. (1989). Adaptive Pattern Recognition and Neural Networks
Addison-Wesley Publishing Company, Inc. (ISBN 0-201-12584-6)
Rumelhart, D. E., Hinton, G. E. and Williams, R. J. (1986). Learning
representations by back-propagating errors. Nature, vol 323 (9 October),
pp. 533-536.
Comments: "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)."
Simpson, P. K. (1990). Artificial Neural Systems: Foundations, Paradigms,
Applications and Implementations. Pergamon Press: New York.
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: New York. (ISBN 0-442-20743-3)
Comments: "Generally considered to be the best introductory text so far.";
"Wasserman flatly enumerates some common architectures from an engineer's
perspective ("how it works") without ever addressing the underlying
fundamentals ("why it works") - important basic concepts such as clustering,
principal components or gradient descent are not treated. It's also full of
errors, and unhelpful diagrams drawn with what appears to be PCB board layout
software from the '70s. For anyone who wants to do active research in the
field I consider it quite inadequate"; "Okay, but too shallow".
Wunsch, D. (Ed.) (July, 1991). Neural Networks: An Introduction.
Pergamon Press.
Zeidenberg. M. (1990). Neural Networks in Artificial Intelligence.
Ellis Horwood, Ltd., Chichester.
Comments: "Gives the AI point of view".
Zornetzer, S. F., Davis, J. L. and Lau, C. (19??). An Introduction to
Neural and Electronic Networks. Academic Press. (ISBN 0-12-781881-2)
Comments: "Covers quite a broad range of topics (collection of
articles/papers )."
--
--Paul Bakker -- email: bakker@cs.uq.oz.au
--Depts. of Computer Science/ Psychology ------
--University of Queensland ---- --------
--New Holland --- ------------- ------------