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An introduction to radial basis functions for system identification: a comparison with other neural network methods

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Warwick, K. and Craddock, R. (1997) An introduction to radial basis functions for system identification: a comparison with other neural network methods. In: 35th IEEE Conference on Decision and Control, 11-13 Dec 1996, Kobe, Japan, pp. 464-469.

Abstract/Summary

A look is taken at the use of radial basis functions (RBFs), for nonlinear system identification. RBFs are firstly considered in detail themselves and are subsequently compared with a multi-layered perceptron (MLP), in terms of performance and usage.

Additional Information Proceedings ISBN: 0780335902
Item Type Conference or Workshop Item (Paper)
URI https://reading-clone.eprints-hosting.org/id/eprint/21649
Item Type Conference or Workshop Item
Refereed Yes
Divisions Science
Uncontrolled Keywords multi-layered perceptron, nonlinear system identification, performance, radial basis functions, usage
Additional Information Proceedings ISBN: 0780335902
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