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Using the correlation criterion to position and shape RBF units for incremental modelling

Record type: Article

A novel technique is proposed for the incremental construction of sparse radial basis function (RBF) networks. The correlation between a RBF regressor and the training data is used as the criterion to position and shape the RBF node, and it is shown that this is equivalent to incrementally minimise the modelling mean square error. A guided random search optimisation method, called the repeated weighted boosting search, is adopted to append RBF nodes one by one in an incremental regression modelling procedure. The experimental results obtained using the proposed method demonstrate that it provides a viable alternative to the existing state-of-the-art modelling techniques for constructing parsimonious RBF models that generalise well.

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Citation

Wang, X.X., Chen, S. and Harris, C.J. (2006) Using the correlation criterion to position and shape RBF units for incremental modelling International Journal of Automation and Computing, 3, (4), pp. 392-403.

More information

Published date: October 2006
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 263141
URI: http://eprints.soton.ac.uk/id/eprint/263141
ISSN: 1476-8186
PURE UUID: 25b78eef-591f-44f5-a207-ca0b843f0f87

Catalogue record

Date deposited: 27 Oct 2006
Last modified: 18 Jul 2017 08:43

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Contributors

Author: X.X. Wang
Author: S. Chen
Author: C.J. Harris

University divisions


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