Article: Exponential stability of high-order bidirectional associative memory neural networks with time delays

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TitleExponential stability of high-order bidirectional associative memory neural networks with time delays
AuthorsCao, J2
Liang, J2
Lam, J1
KeywordsBidirectional Associative Memory (Bam)
Exponential Stability
High-Order Neural Networks
Linear Matrix Inequality
Lyapunov Functional
Time Delays
Issue Date2004
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/physd
CitationPhysica D: Nonlinear Phenomena, 2004, v. 199 n. 3-4, p. 425-436 [How to Cite?]
DOI: http://dx.doi.org/10.1016/j.physd.2004.09.012
AbstractIn this paper, exponential stability is studied for a class of high-order bidirectional associative memory (BAM) neural networks with time delays. By employing the linear matrix inequality (LMI) and the Lyapunov functional methods, several sufficient conditions are obtained for ensuring the system to be globally exponentially stable. Two illustrative examples are also given in the end of this paper to show the effectiveness of our results. © 2004 Elsevier B.V. All rights reserved.
ISSN0167-2789
2011 Impact Factor: 1.594
2011 SCImago Journal Rankings: 0.085
DOIhttp://dx.doi.org/10.1016/j.physd.2004.09.012
ReferencesReferences in Scopus
DC Field
Value
dc.contributor.authorCao, J
dc.contributor.authorLiang, J
dc.contributor.authorLam, J
dc.date.accessioned2012-08-08T08:43:41Z
dc.date.available2012-08-08T08:43:41Z
dc.date.issued2004
dc.description.abstractIn this paper, exponential stability is studied for a class of high-order bidirectional associative memory (BAM) neural networks with time delays. By employing the linear matrix inequality (LMI) and the Lyapunov functional methods, several sufficient conditions are obtained for ensuring the system to be globally exponentially stable. Two illustrative examples are also given in the end of this paper to show the effectiveness of our results. © 2004 Elsevier B.V. All rights reserved.
dc.description.natureLink_to_subscribed_fulltext
dc.identifier.citationPhysica D: Nonlinear Phenomena, 2004, v. 199 n. 3-4, p. 425-436 [How to Cite?]
DOI: http://dx.doi.org/10.1016/j.physd.2004.09.012
dc.identifier.doihttp://dx.doi.org/10.1016/j.physd.2004.09.012
dc.identifier.epage436
dc.identifier.isiWOS:000226128200008
dc.identifier.issn0167-2789
2011 Impact Factor: 1.594
2011 SCImago Journal Rankings: 0.085
dc.identifier.issue3-4
dc.identifier.scopuseid_2-s2.0-10644236158
dc.identifier.spage425
dc.identifier.urihttp://hdl.handle.net/10722/156723
dc.identifier.volume199
dc.languageeng
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/physd
dc.publisher.placeNetherlands
dc.relation.ispartofPhysica D: Nonlinear Phenomena
dc.relation.referencesReferences in Scopus
dc.subjectBidirectional Associative Memory (Bam)
dc.subjectExponential Stability
dc.subjectHigh-Order Neural Networks
dc.subjectLinear Matrix Inequality
dc.subjectLyapunov Functional
dc.subjectTime Delays
dc.titleExponential stability of high-order bidirectional associative memory neural networks with time delays
dc.typeArticle
Author Affiliations
  1. The University of Hong Kong
  2. Southeast University