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Learning noisy patterns in a Hopfield network

Fontanari, J. F. and Meir, R. (1989) Learning noisy patterns in a Hopfield network. Physical Review A, 40 (5). pp. 2806-2809. ISSN 0556-2791. http://resolver.caltech.edu/CaltechAUTHORS:FONpra89

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Abstract

We study the ability of a Hopfield network with a Hebbian learning rule to extract meaningful information from a noisy environment. We find that the network is able to learn an infinite number of ancestor patterns, having been exposed only to a finite number of noisy versions of each. We have also found that there is a regime where the network recognizes the ancestor patterns very well, while performing very poorly on the noisy patterns to which it had been exposed during the learning stage.


Item Type:Article
Additional Information:©1989 The American Physical Society Received 5 June 1989 The research at the California Institute of Technology was supported by Contract No. N00014-87-K-0377 from the U.S. Office of Naval Research. J.F.F. was partly supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico and R.M. is supported by the Weizmann Foundation.
Record Number:CaltechAUTHORS:FONpra89
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:FONpra89
Alternative URL:http://dx.doi.org/10.1103/PhysRevA.40.2806
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:6596
Collection:CaltechAUTHORS
Deposited By: Archive Administrator
Deposited On:14 Dec 2006
Last Modified:26 Dec 2012 09:23

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