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Article: On global asymptotic stability for a class of delayed neural networks

TitleOn global asymptotic stability for a class of delayed neural networks
Authors
KeywordsGlobal Asymptotic Stability
Linear Matrix Inequality
Neural Networks
Neutral Systems
Time-Delay Systems
Issue Date2012
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/1976
Citation
International Journal Of Circuit Theory And Applications, 2012, v. 40 n. 11, p. 1165-1174 How to Cite?
AbstractThis paper deals with the problem of stability analysis for a class of delayed neural networks described by nonlinear delay differential equations of the neutral type. A new and simple sufficient condition guaranteeing the existence, uniqueness and global asymptotic stability of an equilibrium point of such a kind of delayed neural networks is developed by the Lyapunov-Krasovskii method. The condition is expressed in terms of a linear matrix inequality, and thus can be checked easily by recently developed standard algorithms. When the stability condition is applied to the more commonly encountered delayed neural networks, it is shown that our result can be less conservative. Examples are provided to demonstrate the effectiveness of the proposed criteria. © 2011 John Wiley & Sons, Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/157110
ISSN
2015 Impact Factor: 1.179
2015 SCImago Journal Rankings: 0.384
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLam, Jen_US
dc.contributor.authorXu, Sen_US
dc.contributor.authorHo, DWCen_US
dc.contributor.authorZou, Yen_US
dc.date.accessioned2012-08-08T08:45:22Z-
dc.date.available2012-08-08T08:45:22Z-
dc.date.issued2012en_US
dc.identifier.citationInternational Journal Of Circuit Theory And Applications, 2012, v. 40 n. 11, p. 1165-1174en_US
dc.identifier.issn0098-9886en_US
dc.identifier.urihttp://hdl.handle.net/10722/157110-
dc.description.abstractThis paper deals with the problem of stability analysis for a class of delayed neural networks described by nonlinear delay differential equations of the neutral type. A new and simple sufficient condition guaranteeing the existence, uniqueness and global asymptotic stability of an equilibrium point of such a kind of delayed neural networks is developed by the Lyapunov-Krasovskii method. The condition is expressed in terms of a linear matrix inequality, and thus can be checked easily by recently developed standard algorithms. When the stability condition is applied to the more commonly encountered delayed neural networks, it is shown that our result can be less conservative. Examples are provided to demonstrate the effectiveness of the proposed criteria. © 2011 John Wiley & Sons, Ltd.en_US
dc.languageengen_US
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/1976en_US
dc.relation.ispartofInternational Journal of Circuit Theory and Applicationsen_US
dc.subjectGlobal Asymptotic Stabilityen_US
dc.subjectLinear Matrix Inequalityen_US
dc.subjectNeural Networksen_US
dc.subjectNeutral Systemsen_US
dc.subjectTime-Delay Systemsen_US
dc.titleOn global asymptotic stability for a class of delayed neural networksen_US
dc.typeArticleen_US
dc.identifier.emailLam, J:james.lam@hku.hken_US
dc.identifier.authorityLam, J=rp00133en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1002/cta.777en_US
dc.identifier.scopuseid_2-s2.0-84867686248en_US
dc.identifier.hkuros223452-
dc.identifier.isiWOS:000310074600005-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridLam, J=7201973414en_US
dc.identifier.scopusauthoridXu, S=7404438591en_US
dc.identifier.scopusauthoridHo, DWC=7402971938en_US
dc.identifier.scopusauthoridZou, Y=7402166773en_US

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