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Adaptive Neurofuzzy Systems for Difficult Modelling and Control Problems

Record type: Conference or Workshop Item (Other)

This paper briefly describes how neurofuzzy systems combine the linguistic representation of fuzzy logic with the learning abilities and structure of a neural network. Several training algorithms are briefly described and several inductive learning procedures are outlined.

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Citation

Brown, M. and Harris, C.J. (1994) Adaptive Neurofuzzy Systems for Difficult Modelling and Control Problems At Colloq on Advances in Neural Networks for Control and Systems.

More information

Published date: 1994
Additional Information: Organisation: IEE Address: Berlin, Germany
Venue - Dates: Colloq on Advances in Neural Networks for Control and Systems, 1994-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250252
URI: http://eprints.soton.ac.uk/id/eprint/250252
PURE UUID: 48237a93-ebc3-48ee-8461-0969b5df26f1

Catalogue record

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

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Contributors

Author: M. Brown
Author: C.J. Harris

University divisions


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