References

1

Igor Aleksander and Helen Morton. An Introduction to Neural Computing. Chapman and Hall, 1990. An introductory text, slightly idiosyncratic. Good attention to Aleksander's WISARD network.

2

M A Arbib. The Metaphorical Brain, volume 2. Wiley, 1989. An advanced and thorough text, geared to physical and biological effects.

3

R Beale and T Jackson. Neural Computing, an Introduction. Adam Hilger, 1990. General textbook.

4

Adam Blum. Neural Networks Programming in C++. John-Wiley, 1992. Practical book of NN.

5

A Carling. Introducing Neural Networks. Sigma, 1992. General textbook; quite good.

6

Maureen Caudill and Charles Butler. Understanding Neural Networks, Vol I and II. MIT Press, 1991. Practical book of NN.

7

Y Chauvin and D Rumelhart, editors. Back-propagation: Theory, Architectures, and Applications. Lawrence Erlbaum, 1995. Very recent and comprehensive (so good); rather advanced in much of its material.

8

Russell C Eberhart and Roy W Dobbins. Neural Network PC Tools. Academic Press, 1990. Practical book of NN.

9

Laurene Fausett. Fundamentals of Neural Networks. Prentice Hall, 1994. Good general textbook.

10

James A Freeman and David M Skapura. Neural Networks: Algorithms, Applications, and Programming Techniques. Addison-Wesley, 1991. Practical book of NN.

11

Stephen I Gallant. Neural Network Learning and Expert Systems. MIT, 1992. Expert systems and neural networks.

12

Simon Haykin. Neural Networks, A Comprehensive Foundation. Macmillan, 1994. A long and thorough text. Goes quite deep, with a very mathematical treatment; thin on examples.

13

Tarun Khanna. Foundations of Neural netwroks. Addison-Wesley, 1990. An introductory text; perhaps not the most digestible.

14

Granino A Korn. Neural Network Experiments on Personal Computers and Workstations. MIT Press, 1991. Very practical book of NN.

15

Jeannette Lawrence. Introduction to Neural Networks and Expert Systems. California Scientific Software, 1992. Expert systems and neural networks.

16

R Linggard, C Nightingale, and D Myers, editors. Neural networks for vision, speech and natural language. Chapman and Hall, 1992. Summary of BT research projects using NNs.

17

Timothy Masters. Practical Neural Network Recipes in C++. Academic Press, 1993. A cookbook for neural network solutions to practical problems.

18

McClelland and Rumelhart, editors. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Psychological and Biological Models, volume 2. MIT Press, 1986. Instrumental in re-awakening the topic.

19

Nelson M McCord and W T Illingworth. A Practical Guide to Neural Nets. Addison-Wesely, 1990. Practical book of NN.

20

Carver Mead. Analog VLSI and Neural Systems. Addison Wesley, 1989. A hardware text, geared to silicon implementation of biological systems.

21

M Minsky and S Papert. Perceptrons (Second, expanded, edition). MIT, 2 edition, 1988. Updated version of the very influential text that halted perceptron development.

22

B Muller and J Reinhardt. Neural Networks: An Introduction. Springer-Verlag, 1990. Practical book of NN.

23

G A Orchard and W A Phillips. Neural Computation. LEA Ltd, 1990. Practical book of NN.

24

F Rosenblatt. Principles of Neurodynamics. Spartan, New York, 1959. Where it all began.

25

Rumelhart and McClelland, editors. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Foundations, volume 1. MIT Press, 1986. Instrumental in re-awakening the topic.

26

P D Wasserman. Neural computing, Theory and Practice. Van Nostrand, 1989. General textbook.

Papers

We list here the articles that have either been especially influential in the development of the subject (or that part on which we concentrate), or which we regard as especially useful in illustrating particular points. The full Neural Net literature is now absolutely vast and the interested reader is referred elsewhere ....

The following journals may be regarded as the `important' ones, although many others will also publish in this area;

• IEEE Transactions on Neural Networks
• Neural Networks
• Connection Science
• Neural Computation