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Comparative Aspects of Associative Memory Networks for Modelling

Record type: Conference or Workshop Item (Other)

This paper will describe a class of networks called Associative Memory Networks which have many desirable properties for applications within the field of Intelligent Control. This class is defined to include the Albus CMAC neural network, the B-spline neural network and a certain class of Fuzzy Logic networks. These networks will first be described within a common framework which has a natural parallel implementation and then several learning rules will be derived. These are instantaneous gradient descent and error correction adaptive strategies and the sparse internal representation of the networks make them particularly suited to these learning rules. Finally all three networks will be applied to the same nonlinear time series prediction problem, comparing the strengths and weaknesses of each network.

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Citation

An, P.E., Brown, M., Harris, C.J., Lawrence, A.J. and Moore, C.G. (1993) Comparative Aspects of Associative Memory Networks for Modelling At 2nd European Control conference. , pp. 454-459.

More information

Published date: 1993
Additional Information: Address: Groningen, Netherlands
Venue - Dates: 2nd European Control conference, 1993-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250214
URI: http://eprints.soton.ac.uk/id/eprint/250214
PURE UUID: 2d44b18a-d479-41a2-bb8e-15e8b6539ed5

Catalogue record

Date deposited: 04 May 1999
Last modified: 18 Jul 2017 10:43

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Contributors

Author: P.E. An
Author: M. Brown
Author: C.J. Harris
Author: A.J. Lawrence
Author: C.G. Moore

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