Papers on Neural Networks

I have worked in the application of neural networks in robotics, medicine, and the modelling of psychological experiments. I have worked on the theory of supervised, unsupervised, and reinforcement learning.

Bibliography

1

Stephen Marsland, Jonathan Shapiro, and Ulrich Nehmzow.
A self-organising network that grows when required.
Neural Networks, 15(8-9):1041-1058, 2002.
(abstract, full paper).
[At the time this paper was written, we were unaware of similar which we should have referenced. This work is described in A. Baraldi and P. Blonda, "A survey of fuzzy clustering algorithms for pattern recognition: Part II", IEEE Trans. Systems, Man and Cybernetics - Part B: Cybernetics, vol. 29, no. 6, pp. 786-801, Dec. 1999.]

2

J. L. Shapiro and John Wearden.
Reinforcement learning and time perception -- a model of animal experiments.
Advances in Neural Information Processing 14, 2002.
( abstract, full paper).

3

Sybil Hirsch, J. L. Shapiro, and Peter I. Frank.
The application of neural network system techniques to asthma screening and prevalence estimation.
In Cornelius t. Leondes, editor, Handbook of Computational Methods in Biomaterials, Biotechnology, and Biomedical Systems. Kluwer, 2002.

4

Sybil Hirsch, Jonathan Shapiro, Michael Turega, Timothy L. Frank, Robert Niven, and Peter I. Frank.
Using a neural network to screen a population for asthma.
Annals of Epidemiology, 11:369 - 376, 2001.
( full paper).

5

J. L. Shapiro, John Wearden, and Rossano Barone.
A simple model exhibiting scalar timing.
In Robert M. French and Jacques P. Sougnè, editors, Connectionist Models of Learning, Development, and Evolution, Perspectives in Neural Computing. Springer, 2001.
( full paper ).

6

M. Rattray and J. L. Shapiro.
Noisy fitness evaluations in genetic algorithms and the dynamics of learning.
In R. K. Belew and M. D. Vose, editors, Foundations of Genetic Algorithms 4, pages 117 - 139. Morgan Kaufmann, 1997.
( full paper ).

7

Jonathan Foster and Jonathan Shapiro.
Hippocampal and related structures.
In M. Conway, editor, Cognitive Models of Memory. Psychology Press, 1997.

8

Sybil Hirsch, Jonathan Shapiro, and Peter Frank.
Use of an artificial neural network in estimating prevalence and assessing underdiagnosis of asthma.
Neural Computing and Applications, 5:124 - 128, 1997.

9

M. Rattray and J. Shapiro.
The dynamics of genetic algorithms for a simple learning problem.
Journal of Physics: A, 29:7451 - 7473, 1996.
( full paper ).

10

M. Malloch, J. L. Shapiro, G. Hitch, V. Culpin, and J. Towse.
Temporal effects in immediate verbal memory: A combined experimental modelling approach.
Language and Cognitive Processes, 10(3-4):401 - 405, 1995.

11

Jonathan Shapiro and Adam Prügel-Bennett.
Non-linear statistical analysis and self-organizing Hebbian networks'.
Advances in Neural Information Processing, 6:407 - 414, 1994.

12

Adam Prügel-Bennett and Jonathan Shapiro.
Statistical mechanics of unsupervised Hebbian learning.
Journal of Physics A, 26:2343 - 2396, 1993.

13

Adam Prügel-Bennett and Jonathan Shapiro.
The partitioning problem in unsupervised learning for non-linear neurons.
Journal of Physics A, 26:7417 - 7426, 1993.

14

Jonathan Shapiro and Adam Prügel-Bennett.
Unsupervised Hebbian learning,.
In J. Bower and F. Eeckmann, editors, Computation and Neural Systems, pages 25 - 30. Kluwer Academic Publishers, 1993.

15

Jonathan Shapiro and Adam Prügel-Bennett.
Unsupervised learning and the shape of the neuron activation function.
In I. Aleksander and J. Taylor, editors, Artificial Neural Networks II, pages 179 - 182. Elsevier Science Publishers, 1992.

16

Jonathan Shapiro, Hojung Cha, and Ron Daniels Jr.
Parallel machine simulation for the design of architectures for neural networks.
In K. Boyanov, editor, Proceedings of the 3rd Workshop on Parallel and Distributed Processing, pages 323 - 332. Elsvier Scientific Publisher, 1992.

17

Neil Burgess, J. L. Shapiro, and M. A. Moore.
Neural network models of list learning.
Network: Computation in Neural Systems, 4(2):399 - 422, 1991.

18

Neil Burgess, M. A. Moore, and J. L. Shapiro.
Human-like forgetting in neural network models of memory.
In W. K. Theumann and R. Koberle, editors, Neural Networks and Spin Glasses. World Scientific,, 1990.

19

J. L. Shapiro.
Hard learning in boolean neural networks.
In J.G. Taylor, editor, Neural Computing. IOP Publishing LTD, 1989.

20

J. L. Shapiro.
A solvable model of hard learning.
In L. Personnaz and G. Dreyfus, editors, Neural Networks, From Models to Applications. IDSET, 1988.

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