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. (eds.) Methods and Applications of Intelligent Control. , Kluwer Academic, 283-303.
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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|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Southampton Wireless Group
Faculty of Physical Sciences and Engineering > Electronics and Computer Science
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > IT Innovation Centre
|Date Deposited:||21 Mar 2003|
|Last Modified:||31 Mar 2016 13:50|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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