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


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), 392-403.

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Description/Abstract

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.

Item Type: Article
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
ePrint ID: 263141
Date Deposited: 27 Oct 2006
Last Modified: 27 Mar 2014 20:06
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/263141

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