Article: Robust synchronization criteria for recurrent neural networks via linear feedback

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TitleRobust synchronization criteria for recurrent neural networks via linear feedback
AuthorsHuang, X1 2
Lam, J3
Cao, J2
Xu, S4
KeywordsLinear Matrix Inequality
Lyapunov-Krasovskii Function
Recurrent Neural Networks
Robust Synchronization
Issue Date2007
PublisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijbc/ijbc.shtml
CitationInternational Journal Of Bifurcation And Chaos, 2007, v. 17 n. 8, p. 2723-2738 [How to Cite?]
DOI: http://dx.doi.org/10.1142/S0218127407018713
AbstractIn this paper, the robust synchronization problem is addressed for recurrent neural networks with time-varying delay by linear feedback control. Robustness in the present paper is referred to as the allowance of parameters mismatch between the drive system and the response system. Sufficient conditions for robust synchronization with a synchronization error bound, expressed as linear matrix inequality (LMI), are derived based on Lyapunov-Krasovskii functionals. Both delay-dependent and delay-independent conditions are obtained. Two examples are given to illustrate the results. © World Scientific Publishing Company.
ISSN0218-1274
2011 Impact Factor: 0.755
2011 SCImago Journal Rankings: 0.058
DOIhttp://dx.doi.org/10.1142/S0218127407018713
ISI Accession Number IDWOS:000253285200013
ReferencesReferences in Scopus
DC Field
Value
dc.contributor.authorHuang, X
dc.contributor.authorLam, J
dc.contributor.authorCao, J
dc.contributor.authorXu, S
dc.date.accessioned2012-08-08T08:44:33Z
dc.date.available2012-08-08T08:44:33Z
dc.date.issued2007
dc.description.abstractIn this paper, the robust synchronization problem is addressed for recurrent neural networks with time-varying delay by linear feedback control. Robustness in the present paper is referred to as the allowance of parameters mismatch between the drive system and the response system. Sufficient conditions for robust synchronization with a synchronization error bound, expressed as linear matrix inequality (LMI), are derived based on Lyapunov-Krasovskii functionals. Both delay-dependent and delay-independent conditions are obtained. Two examples are given to illustrate the results. © World Scientific Publishing Company.
dc.description.natureLink_to_subscribed_fulltext
dc.identifier.citationInternational Journal Of Bifurcation And Chaos, 2007, v. 17 n. 8, p. 2723-2738 [How to Cite?]
DOI: http://dx.doi.org/10.1142/S0218127407018713
dc.identifier.doihttp://dx.doi.org/10.1142/S0218127407018713
dc.identifier.epage2738
dc.identifier.isiWOS:000253285200013
dc.identifier.issn0218-1274
2011 Impact Factor: 0.755
2011 SCImago Journal Rankings: 0.058
dc.identifier.issue8
dc.identifier.scopuseid_2-s2.0-34748850646
dc.identifier.spage2723
dc.identifier.urihttp://hdl.handle.net/10722/156918
dc.identifier.volume17
dc.languageeng
dc.publisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijbc/ijbc.shtml
dc.publisher.placeSingapore
dc.relation.ispartofInternational Journal of Bifurcation and Chaos
dc.relation.referencesReferences in Scopus
dc.subjectLinear Matrix Inequality
dc.subjectLyapunov-Krasovskii Function
dc.subjectRecurrent Neural Networks
dc.subjectRobust Synchronization
dc.titleRobust synchronization criteria for recurrent neural networks via linear feedback
dc.typeArticle
Author Affiliations
  1. Shandong University of Science and Technology
  2. Southeast University
  3. City University of Hong Kong
  4. Nanjing University of Science and Technology