Abstract
A fundamental difficulty when using neural networks applied to pattern recognition, is the problem of stimulus equivalence — the invariance of symbolic information independent of transformation within a search space. For example, symbolically, the letter A remains an A irrespective of its position, size or orientation within an image field. Adult humans can generally recognise patterns accurately, despite such transformations and distortions. Classically it has been hypothesised that this ability is due to a normalisation process that occurs before the classification process begins.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Hinton G. E.: ‘A parallel computation that assigns canonical object based frames of reference’, Proc 7th IJCAI (1981).
McClelland J. L.: ‘Retrieving general and specific knowledge from stored knowledge of specifics’, Proc 3rd Conf Cognitive Society, Berkeley, CA (1981).
Bishop J. M.: ‘Stochastic searching networks’, Proc 1st IEE Conf on Artificial Neural Networks, pp 329–331, London (1989).
Bishop J. M.: ‘Anarchic techniques for pattern classification’, PhD Thesis, Reading University, pp 5–14 (1989).
Cox D. R. & Miller H. D.: ‘The theory of stochastic processes’, Chapter 3, Chapman & Hall, London (1965).
Cox D. R. & Miller H. D.: ‘The theory of stochastic processes’, Chapman & Hall, London pp 79, (1965).
Welsh W. J., Woodland P. C. & Myers D. J.: ‘A set of test problems for assessing neural net algorithms’, BTL, Martlesham Heath, UK (1989).
Bledsoe W. W. & Browning I.: ‘Pattern recognition and reading by machine’, Proceedings of the Eastern Joint Computer Conference, pp 225–232 (1959).
Aleksander I., Thomas W. V. & Bowden P. A.: ‘WISARD: a radical step forward in image recognition’, Sensor Review, (July 1984).
Aleksander I. & Stonham T. J.: ‘Guide to pattern recognition using random access memories’, Computers & Digital Techniques, 2, No 1, pp 29–40 (1979).
Bishop J. M., Minehinton P. R. & Mitchell R. J.: ‘The Minchinton cell — Analogue input to the n-tuple net’, Proc INNC’ 90, Paris (1990).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1992 British Telecommunications plc
About this chapter
Cite this chapter
Bishop, J.M., Torr, P. (1992). The Stochastic Search Network. In: Linggard, R., Myers, D.J., Nightingale, C. (eds) Neural Networks for Vision, Speech and Natural Language. BT Telecommunications Series, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-2360-0_24
Download citation
DOI: https://doi.org/10.1007/978-94-011-2360-0_24
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-5041-8
Online ISBN: 978-94-011-2360-0
eBook Packages: Springer Book Archive