Adaptive Neurofuzzy Systems for Difficult Modelling and Control Problems
Brown, M. and Harris, C.J. (1994) Adaptive Neurofuzzy Systems for Difficult Modelling and Control Problems. Colloq on Advances in Neural Networks for Control and Systems
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Description/Abstract
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.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Additional Information: | Organisation: IEE Address: Berlin, Germany |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 250252 |
| Date Deposited: | 04 May 1999 |
| Last Modified: | 02 Mar 2012 13:18 |
| Contributors: | Brown, M. (Author) Harris, C.J. (Author) |
| Date: | 1994 |
| Additional Information: | Organisation: IEE Address: Berlin, Germany |
| Status: | Published |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/250252 |
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