A Comparison of the Backpropagation and Recursive Prediction Error Algorithms for Training Neural Networks.
Billings, S.A., Jamaluddin, H.D. and Chen, S.
(1990)
A Comparison of the Backpropagation and Recursive Prediction Error Algorithms for Training Neural Networks.
Research Report.
Acse Report 379
.
Dept of Automatic Control and System Engineering. University of Sheffield
Abstract
A new recursive prediction error routine is compared with the backpropagation method of training neural networks. Results based on simulated systems, the prediction of Canadian Lynx data and the modelling of an automotive diesel engine indicate that the recursive prediction error algorithm is far superior to backpropagation.
Metadata
Item Type:
Monograph
Authors/Creators:
Billings, S.A.
Jamaluddin, H.D.
Chen, S.
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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