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

Download

Full text not available from this repository.

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 Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
ePrint ID: 250252
Date Deposited: 04 May 1999
Last Modified: 27 Mar 2014 19:51
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/250252

Actions (login required)

View Item View Item