The University of Southampton
University of Southampton Institutional Repository

On the Condition of Adaptive Neurofuzzy Models

Brown, M., An, P.E. and Harris, C.J. (1995) On the Condition of Adaptive Neurofuzzy Models At Int. Joint Conf. of the 4th Int. Conf. on Fuzzy Systems and the 2nd Int. Fuzzy Engineering Symp.. , 663--670.

Record type: Conference or Workshop Item (Other)

Abstract

Learning within fuzzy and neurofuzzy systems is becomingly increasingly important as researchers try to infer qualitative, vague information from quantitative, numeric data. The fuzzy representation of an adaptive neurofuzzy system is important both for initialisation and validation purposes, where a designer needs to interpret the knowledge stored in a network. Therefore it is important to study the convergence and rate of convergence characteristics of the parameters in a neurofuzzy model and investigate how this depends on the system's structure. This paper considers how the condition of the input fuzzy sets determines the convergence and generalisation abilities of the network and describes several new results about instantaneous least mean square training rules.

Full text not available from this repository.

More information

Published date: 1995
Additional Information: Organisation: IEEE/IFES Address: Yokohama, Japan
Venue - Dates: Int. Joint Conf. of the 4th Int. Conf. on Fuzzy Systems and the 2nd Int. Fuzzy Engineering Symp., 1995-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250243
URI: http://eprints.soton.ac.uk/id/eprint/250243
PURE UUID: 48036180-91c6-454a-936c-489652ff3d3c

Catalogue record

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

Export record

Contributors

Author: M. Brown
Author: P.E. An
Author: C.J. Harris

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×