Neurofuzzy Model Construction for the Modelling of Non-linear Processes
Bossley, K.M., Brown, M. and Harris, C.J. (1995) Neurofuzzy Model Construction for the Modelling of Non-linear Processes. 3rd European Control conference , 2438--2443.
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Description/Abstract
Neurofuzzy systems are ideal for modelling nonlinear processes; combining the transparent knowledge representation of fuzzy systems with the well established learning techniques of associative memory networks. In the control community there is a need for high-dimensional modelling, but unfortunately these neurofuzzy systems suffer from the curse of dimensionality. To make the use of high-dimensional neurofuzzy systems practical, off-line construction algorithms need to be developed which generate parsimonious models. This need for off-line construction algorithms is enhanced by the lack of expert knowledge from which models are traditionally developed. This paper outlines the concepts of B-spline neurofuzzy systems and presents several representations which can be exploited to produce parsimonious models. Finally, an off-line construction algorithm based on several of these representations is illustrated with a simple example.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Additional Information: | Address: Rome, Italy |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 250234 |
| Date Deposited: | 04 May 1999 |
| Last Modified: | 02 Mar 2012 13:17 |
| Contributors: | Bossley, K.M. (Author) Brown, M. (Author) Harris, C.J. (Author) |
| Date: | 1995 |
| Additional Information: | Address: Rome, Italy |
| Status: | Published |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/250234 |
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