Intelligent Neurofuzzy Estimators and Multisensor Data Fusion


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

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Description/Abstract

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.

Item Type: Book Section
Additional Information: (no figures in on-line version) Chapter: 10 Address: Netherlands
ISSNs: 0792346246
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
Faculty of Physical Sciences and Engineering > Electronics and Computer Science
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > IT Innovation Centre
ePrint ID: 250032
Date Deposited: 21 Mar 2003
Last Modified: 27 Mar 2014 19:50
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/250032

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