The University of Southampton
University of Southampton Institutional Repository

Intelligent Neurofuzzy Estimators and Multisensor Data Fusion

Record type: Book Section

Multi-Sensor Data Fusion (MSDF), or the process of fusing data from a variety of disparate data sources about a single entity, feature or system state, is of prime importance in the monitoring and control of complex systems. This paper addresses the basic subproblems of MSDF within a unified informational framework derived via Neurofuzzy modelling and estimation algorithms. This environment provides a common framework for integrating information which is database, sensor based, experiemental based and mechanistic. The paper introduces parsimonious neurofuzzy modelling algorithms and utilises them in generating local state estimators which are optimal in information processing. A MSDF system utilises these algorithms in a distributed decentralised architecture.

Full text not available from this repository.

Citation

Harris, C.J., Wu, Z.Q., Bossley, K.M. and Brown, M. (1997) Intelligent Neurofuzzy Estimators and Multisensor Data Fusion In, Tzafestas, S.G. (eds.) Methods and Applications of Intelligent Control. Kluwer Academic pp. 283-303.

More information

Published date: 1997
Additional Information: (no figures in on-line version) Chapter: 10 Address: Netherlands
Venue - Dates: Methods and Applications of Intelligent Control, 1997-01-01
Organisations: Electronics & Computer Science, IT Innovation, Southampton Wireless Group

Identifiers

Local EPrints ID: 250032
URI: http://eprints.soton.ac.uk/id/eprint/250032
PURE UUID: f29950f7-e881-4013-a5dc-d19c462a359b

Catalogue record

Date deposited: 21 Mar 2003
Last modified: 18 Jul 2017 10:44

Export record

Contributors

Author: C.J. Harris
Author: Z.Q. Wu
Author: K.M. Bossley
Author: M. Brown
Editor: S.G. Tzafestas

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.

×