Construction of tunable radial basis function networks using orthogonal forward selection
Chen, Sheng, Hong, Xia, Luk, Bing L. and Harris, Chris J. (2009) Construction of tunable radial basis function networks using orthogonal forward selection. IEEE Transactions on Systems, Man, and Cybernetics - Part B, 39, (2), 457-466.
- Published Version
An orthogonal forward selection (OFS) algorithm based on leave-one-out (LOO) criteria is proposed for the construction of radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines a RBF node, namely its centre vector and diagonal covariance matrix, by minimising the LOO statistics. For regression application, the LOO criterion is chosen to be the LOO mean square error, while the LOO misclassification rate is adopted in two-class classification application. This OFS-LOO algorithm is computationally efficient and it is capable of constructing parsimonious RBF networks that generalise well. Moreover, the proposed algorithm is fully automatic and the user does not need to specify a termination criterion for the construction process. The effectiveness of the proposed RBF network construction procedure is demonstrated using examples taken from both regression and classification applications.
|Divisions:||Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||20 Mar 2009 16:14|
|Last Modified:||23 Aug 2012 03:33|
|Contributors:||Chen, Sheng (Author)
Hong, Xia (Author)
Luk, Bing L. (Author)
Harris, Chris J. (Author)
|Further Information:||Google Scholar|
|ISI Citation Count:||12|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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