Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/77895
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dc.contributor.authorWu, Z.-
dc.contributor.authorShi, P.-
dc.contributor.authorSu, H.-
dc.contributor.authorChu, J.-
dc.date.issued2012-
dc.identifier.citationExpert Systems with Applications, 2012; 39(6):6174-6181-
dc.identifier.issn0957-4174-
dc.identifier.issn1873-6793-
dc.identifier.urihttp://hdl.handle.net/2440/77895-
dc.description.abstractThe problem of delay-dependent stability analysis is investigated for discrete-time Markovian jump neural networks with mixed time-delays (both discrete and infinity-distributed time delays). The Markov chain in the underlying neural networks is finite piecewise homogeneous. A delay-dependent condition is derived for the addressed neural networks to be globally asymptotically stable. As an extension, we further consider the stability analysis problem for the same type of neural networks but with partially known transition probabilities. Two numerical examples are given to demonstrate the usefulness of the derived methods. © 2011 Elsevier Ltd. All rights reserved.-
dc.description.statementofresponsibilityZheng-Guang Wu, Peng Shi, Hongye Su, Jian Chu-
dc.language.isoen-
dc.publisherPergamon-Elsevier Science Ltd-
dc.rights© 2011 Elsevier Ltd. All rights reserved.-
dc.source.urihttp://dx.doi.org/10.1016/j.eswa.2011.11.111-
dc.subjectNeural networks-
dc.subjectMarkovian jumping parameters-
dc.subjectMixed time-delays-
dc.subjectPiecewise homogeneous-
dc.subjectGlobally asymptotically stable-
dc.titleStability analysis for discrete-time Markovian jump neural networks with mixed time-delays-
dc.typeJournal article-
dc.identifier.doi10.1016/j.eswa.2011.11.111-
pubs.publication-statusPublished-
dc.identifier.orcidShi, P. [0000-0001-6295-0405] [0000-0001-8218-586X] [0000-0002-0864-552X] [0000-0002-1358-2367] [0000-0002-5312-5435]-
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