Neural Networks for Nonlinear Dynamic System Modelling and Identification
Chen, S. and Billings, S.A.
(1991)
Neural Networks for Nonlinear Dynamic System Modelling and Identification.
Research Report.
Acse Report 436
.
Dept of Automatic Control and System Engineering. University of Sheffield
Abstract
Many real-world systems exhibit complex non-linear characteristics and cannot be treated satisfactorily using linear systems theory. A neural network which has the ability to learn sophisticated non-linear relationships provides an ideal means of modelling complicated non-linear systems. This paper addresses the issues related to the identification of non-linear discrete-time dynamic systems using neural networks..........
Metadata
Item Type:
Monograph
Authors/Creators:
Chen, S.
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.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)