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Article: Robust stability for interval stochastic neural networks with time-varying discrete and distributed delays

TitleRobust stability for interval stochastic neural networks with time-varying discrete and distributed delays
Authors
KeywordsInterval systems
Neural networks
Robust stability
Stochastic systems
Time-varying delays
Issue Date2011
PublisherSpringer (India) Private Ltd. The Journal's web site is located at http://www.springer.com/math/journal/12591
Citation
Differential Equations and Dynamical Systems, 2011, v. 19 n. 1-2, p. 97-118 How to Cite?
AbstractThis paper investigates the problem of robust stability for a class of stochastic interval neural networks with discrete and distributed time-varying delays. The discrete delays are assumed to be varying within a given interval, while the parameter uncertainties are assumed to be bounded in some given compact sets. Based on the Itô differential formula and stochastic stability theory, delay-range-dependent criteria for stochastic interval neural networks with time-varying delays are derived to guarantee robust global asymptotic stability in mean square. In this paper, when estimating the upper bound of the derivative of Lyapunov functionals, we are concerned with better handling of terms related to the discrete and distributed delays and establishing less conservative results. These robust stability conditions are presented in terms of linear matrix inequalities and can be efficiently solved via standard numerical software. An important feature of the results proposed in this paper is that the stability conditions are dependent on the upper and lower bounds of the discrete delays. Numerical examples are given to illustrate the effectiveness of the proposed method. © 2010 Foundation for Scientific Research and Technological Innovation.
Persistent Identifierhttp://hdl.handle.net/10722/139424
ISSN
2015 SCImago Journal Rankings: 0.475

 

DC FieldValueLanguage
dc.contributor.authorLi, Hen_US
dc.contributor.authorCheung, KCen_US
dc.contributor.authorLam, Jen_US
dc.contributor.authorGao, Hen_US
dc.date.accessioned2011-09-23T05:49:19Z-
dc.date.available2011-09-23T05:49:19Z-
dc.date.issued2011en_US
dc.identifier.citationDifferential Equations and Dynamical Systems, 2011, v. 19 n. 1-2, p. 97-118en_US
dc.identifier.issn0971-3514-
dc.identifier.urihttp://hdl.handle.net/10722/139424-
dc.description.abstractThis paper investigates the problem of robust stability for a class of stochastic interval neural networks with discrete and distributed time-varying delays. The discrete delays are assumed to be varying within a given interval, while the parameter uncertainties are assumed to be bounded in some given compact sets. Based on the Itô differential formula and stochastic stability theory, delay-range-dependent criteria for stochastic interval neural networks with time-varying delays are derived to guarantee robust global asymptotic stability in mean square. In this paper, when estimating the upper bound of the derivative of Lyapunov functionals, we are concerned with better handling of terms related to the discrete and distributed delays and establishing less conservative results. These robust stability conditions are presented in terms of linear matrix inequalities and can be efficiently solved via standard numerical software. An important feature of the results proposed in this paper is that the stability conditions are dependent on the upper and lower bounds of the discrete delays. Numerical examples are given to illustrate the effectiveness of the proposed method. © 2010 Foundation for Scientific Research and Technological Innovation.-
dc.languageengen_US
dc.publisherSpringer (India) Private Ltd. The Journal's web site is located at http://www.springer.com/math/journal/12591-
dc.relation.ispartofDifferential Equations and Dynamical Systemsen_US
dc.rightsThe original publication is available at www.springerlink.com-
dc.subjectInterval systems-
dc.subjectNeural networks-
dc.subjectRobust stability-
dc.subjectStochastic systems-
dc.subjectTime-varying delays-
dc.titleRobust stability for interval stochastic neural networks with time-varying discrete and distributed delaysen_US
dc.typeArticleen_US
dc.identifier.emailCheung, KC: kccheung@hkucc.hku.hken_US
dc.identifier.emailLam, J: james.lam@hku.hken_US
dc.identifier.authorityCheung, KC=rp01322en_US
dc.identifier.authorityLam, J=rp00133en_US
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s12591-010-0075-x-
dc.identifier.scopuseid_2-s2.0-80053383188-
dc.identifier.hkuros196459en_US
dc.identifier.volume19en_US
dc.identifier.issue1-2en_US
dc.identifier.spage97en_US
dc.identifier.epage118en_US
dc.identifier.eissn0974-6870-
dc.publisher.placeIndia-

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