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Article: A new LMI condition for delay-dependent asymptotic stability of delayed Hopfield neural networks

TitleA new LMI condition for delay-dependent asymptotic stability of delayed Hopfield neural networks
Authors
KeywordsGlobal asymptotic stability
Hopfield neural networks
Linear matrix inequality
Time delays
Issue Date2006
PublisherIEEE.
Citation
IEEE Transactions On Circuits And Systems Ii: Express Briefs, 2006, v. 53 n. 3, p. 230-234 How to Cite?
AbstractIn this paper, a new delay-dependent asymptotic stability condition for delayed Hopfield neural networks is given in terms of a linear matrix inequality, which is less conservative than existing ones in the literature. This condition guarantees the existence of a unique equilibrium point and its global asymptotic stability of a given delayed Hopfield neural network. Examples are provided to show the reduced conservatism of the proposed condition. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/44940
ISSN
2006 Impact Factor: 0.922
2007 SCImago Journal Rankings: 1.092
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorXu, Sen_HK
dc.contributor.authorLam, Jen_HK
dc.contributor.authorHo, DWCen_HK
dc.date.accessioned2007-10-30T06:13:55Z-
dc.date.available2007-10-30T06:13:55Z-
dc.date.issued2006en_HK
dc.identifier.citationIEEE Transactions On Circuits And Systems Ii: Express Briefs, 2006, v. 53 n. 3, p. 230-234en_HK
dc.identifier.issn1057-7130en_HK
dc.identifier.urihttp://hdl.handle.net/10722/44940-
dc.description.abstractIn this paper, a new delay-dependent asymptotic stability condition for delayed Hopfield neural networks is given in terms of a linear matrix inequality, which is less conservative than existing ones in the literature. This condition guarantees the existence of a unique equilibrium point and its global asymptotic stability of a given delayed Hopfield neural network. Examples are provided to show the reduced conservatism of the proposed condition. © 2006 IEEE.en_HK
dc.format.extent149469 bytes-
dc.format.extent10566 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE Transactions on Circuits and Systems II: Express Briefsen_HK
dc.rights©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectGlobal asymptotic stabilityen_HK
dc.subjectHopfield neural networksen_HK
dc.subjectLinear matrix inequalityen_HK
dc.subjectTime delaysen_HK
dc.titleA new LMI condition for delay-dependent asymptotic stability of delayed Hopfield neural networksen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1549-7747&volume=53&issue=3&spage=230&epage=234&date=2006&atitle=A+new+LMI+condition+for+delay-dependent+asymptotic+stability+of+delayed+Hopfield+neural+networksen_HK
dc.identifier.emailLam, J:james.lam@hku.hken_HK
dc.identifier.authorityLam, J=rp00133en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TCSII.2005.857764en_HK
dc.identifier.scopuseid_2-s2.0-33644993005en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33644993005&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume53en_HK
dc.identifier.issue3en_HK
dc.identifier.spage230en_HK
dc.identifier.epage234en_HK
dc.identifier.isiWOS:000236215200014-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridXu, S=7404438591en_HK
dc.identifier.scopusauthoridLam, J=7201973414en_HK
dc.identifier.scopusauthoridHo, DWC=7402971938en_HK

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