Fast Orthogonal Identification of Nonlinear Stochastic Models and Radial Basis Function Neural Networks
Zhu, Q.M. and Billings, S.A.
(1994)
Fast Orthogonal Identification of Nonlinear Stochastic Models and Radial Basis Function Neural Networks.
Research Report.
ACSE Research Report 526
.
Department of Automatic Control and Systems Engineering
Abstract
A new fast orthogonal estimation algorithm is derived for a wide class of nonlinear stochastic models including training radial basis function neural networks. The selection of significant regressors and the estimation of unknown parameters in the presence of nonlinear noise sources are considered and simulated examples are included to demonstrate the efficiency of the new procedure.
Metadata
Item Type:
Monograph
Authors/Creators:
Zhu, Q.M.
Billings, S.A.
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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