Non-Linear Systems Identification Using Radial Basis Functions
Chen, S., Billings, S.A., Cowan, C.F.N. et al. (1 more author)
(1989)
Non-Linear Systems Identification Using Radial Basis Functions.
Research Report.
Acse Report 378
.
Dept of Automatic Control and System Engineering. University of Sheffield
Abstract
This paper investigates the identification of discrete-time non-linear systems using radial basis functions. A forward regression algorithm based on an orthogonal decomposition of the regression matrix is employed to select a suitable set of radial-basis-function centres from a large number of possible candidates and this provides, for the first time, a fully automatic selection procedure for identifying parsimonious radial-basis-function models of structure-unknown non-linear systems. The relationship between neural networks and radial basis functions is discussed and the application of the algorithms to real data is included to demonstrate the effectiveness of this approach.
Metadata
Item Type:
Monograph
Authors/Creators:
Chen, S.
Billings, S.A.
Cowan, C.F.N.
Grant, P.M.
Copyright, Publisher and Additional Information:
The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
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