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dc.contributor.author박주현ko
dc.contributor.author오쟁광ko
dc.contributor.authorH. Su[H. Su]ko
dc.contributor.authorJ. Chu[J. Chu]ko
dc.date.accessioned2015-12-17T02:09:19Z-
dc.date.available2015-12-17T02:09:19Z-
dc.date.created2015-11-13-
dc.date.issued201210-
dc.identifier.citationNONLINEAR ANALYSIS-REAL WORLD APPLICATIONS, v.13, no.5, pp.2423 - 2431-
dc.identifier.issn1468-1218-
dc.identifier.urihttp://hdl.handle.net/YU.REPOSITORY/27154-
dc.identifier.urihttp://dx.doi.org/10.1016/j.nonrwa.2012.02.009-
dc.description.abstractIn this paper, passivity analysis is considered for Markov jump neural networks with both mixed time-delays and time-varying transition rates. The mixed time-delays consist of both discrete and distributed delays. The time-varying character of transition rates is assumed to be piecewise-constant. By use of the linear matrix inequality (LMI) method and a Lyapunov functional that accounts for the mixed time-delays, a delay-dependent passivity condition is derived, which can be easily checked. The result presented depends upon not only discrete delay but also distributed delay. A numerical example is proposed to show the effectiveness of the proposed method. (C) 2012 Elsevier Ltd. All rights reserved.-
dc.language영어-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.subjectEXPONENTIAL STABILITY-
dc.subjectDISTRIBUTED DELAYS-
dc.subjectVARYING DELAY-
dc.subjectDISSIPATIVITY ANALYSIS-
dc.subjectSINGULAR SYSTEMS-
dc.subjectASYMPTOTIC STABILITY-
dc.subjectSTATE ESTIMATION-
dc.subjectDISCRETE-
dc.subjectPARAMETERS-
dc.subjectSYNCHRONIZATION-
dc.titlePassivity analysis of Markov jump neural networks with mixed time-delays and piecewise-constant transition rates-
dc.typeArticle-
dc.identifier.wosid000303092400036-
dc.identifier.scopusid2-s2.0-84862816895-
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