Non-Linear Systems Identification Using Neural Networks
Chen, S., Billings, S.A. and Grant, P.M.
(1989)
Non-Linear Systems Identification Using Neural Networks.
Research Report.
Acse Report 370
.
Dept of Automatic Control and System Engineering. University of Sheffield
Abstract
Multi-layered neural networks offer an exciting alternative for modelling complex non-linear systems. This paper investigates the identification of discrete-time non-linear systems using neural networks with a single hidden layer. New parameter estimation algorithms are derived for the neural network model based on a prediction error formulation and the application to both simulated and real data is included to demonstrate the effectiveness of the neural network 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.
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