A Recursive Hybrid Algorithm for Non-Linear System Identification Using Radial Basis Function Networks
Chen, S., Billings, S.A. and Grant, P.M.
(1991)
A Recursive Hybrid Algorithm for Non-Linear System Identification Using Radial Basis Function Networks.
Research Report.
Acse Report 422
.
Dept of Automatic Control and System Engineering. University of Sheffield
Abstract
Recursive identification of non-linear systems is investigated using radial basis function networks. A novel approach is adopted which employs a hybrid clustering and least squares algorithm. The recursive clustering algorithm adjusts the centres of the radial basis function network, while the recursive least squares algorithm estimates the connection weights of the network. This hybrid algorithm significantly enhances the real-time or adaptive capability of radial basis function models. The application to simulated and real data are included to demonstrate the effectiveness of this hybrid approach.
Metadata
Item Type:
Monograph
Authors/Creators:
Chen, S.
Billings, S.A.
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.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)