Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/86189
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dc.contributor.authorWu, M.-
dc.contributor.authorLiu, F.-
dc.contributor.authorShi, P.-
dc.contributor.authorHe, Y.-
dc.contributor.authorYokoyama, R.-
dc.date.issued2008-
dc.identifier.citationIEEE Transactions on Circuits and Systems, Part 2: Express Briefs, 2008; 55(7):690-694-
dc.identifier.issn1549-7747-
dc.identifier.issn1558-3791-
dc.identifier.urihttp://hdl.handle.net/2440/86189-
dc.description.abstractThis paper deals with the problem of exponential stability for a class of discrete-time recurrent neural networks with time-varying delay by employing an improved free-weighting matrix approach. The relationship among the time-varying delay, its upper bound and their difference is taken into account. As a result, a new and less conservative delay-dependent stability criterion is obtained without ignoring any useful terms on the difference of a Lyapunov function, which is expressed in terms of linear matrix inequalities. Finally, numerical examples are given to demonstrate the effectiveness of the proposed techniques.-
dc.description.statementofresponsibilityMin Wu, Fang Liu, Peng Shi, Yong He and Ryuichi Yokoyama-
dc.language.isoen-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.rights© 2008 IEEE-
dc.source.urihttp://dx.doi.org/10.1109/tcsii.2008.921597-
dc.subjectDiscrete-time recurrent neural networks-
dc.subjecttime-varying delay-
dc.subjectdelay-dependent stability-
dc.subjectLyapunov function-
dc.subjectlinear matrix inequalities (LMIs)-
dc.titleImproved free-weighting matrix approach for stability analysis of discrete-time recurrent neural networks with time-varying delay-
dc.typeJournal article-
dc.identifier.doi10.1109/TCSII.2008.921597-
pubs.publication-statusPublished-
dc.identifier.orcidShi, P. [0000-0001-8218-586X]-
Appears in Collections:Aurora harvest 2
Electrical and Electronic Engineering publications

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