Lyapunov stability-based adaptive backpropagation for discrete time system

Zhihong Man, Serig Kah Phooi, H. R. Wu

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

4 Citations (Scopus)

Abstract

Lyapunov stability-based adaptive backpropagation (LABP) for discrete systems is proposed in this paper. It can be applied to various aspects of adaptive signal processing. A Lyapunov function of the error between the desired and actual outputs of the neural network is first defined. Then the error is backward-propagated based on Lyapunov stability theory so that it can be used to adaptively adjust the weights of the inner layers of the neural networks. Subsequently, this will lead to an error between the desired and actual outputs converging to zero asymptotically. The proposed scheme possesses distinct advantages over the conventional BP by assuring that the system will not get stuck in local minima. Furthermore, this scheme has a faster convergence property and the stability is guaranteed by Lyapunov stability theory. A simulation example is performed to support the proposed scheme.

Original languageEnglish
Title of host publicationISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications
PublisherIEEE Computer Society
Pages661-664
Number of pages4
ISBN (Print)1864354518, 9781864354515
DOIs
Publication statusPublished - 1999
Externally publishedYes
Event5th International Symposium on Signal Processing and Its Applications, ISSPA 1999 - Brisbane, QLD, Australia
Duration: 22 Aug 199925 Aug 1999

Publication series

NameISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications
Volume2

Conference

Conference5th International Symposium on Signal Processing and Its Applications, ISSPA 1999
Country/TerritoryAustralia
CityBrisbane, QLD
Period22/08/9925/08/99

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