Robust stability analysis for fuzzy stochastic Hopfield neural networks with time–varying delays

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dc.contributor.authorGopalakrishnan, N.
dc.contributor.departmentOthertr_TR
dc.contributor.facultyOthertr_TR
dc.date.accessioned2021-11-29T12:11:17Z
dc.date.available2021-11-29T12:11:17Z
dc.date.issued2020-12-31
dc.description.abstractThis paper investigates the delay-dependent robust stability problem of fuzzy stochastic Hopfield neural networks with random timevarying delays. Moreover, in this paper, the stochastic delay is assumed to satisfy a certain probability distribution. By introducing a stochastic variable with Bernoulli distribution, the neural networks with random time delays is transformed into one with deterministic delays and stochastic parameters. Based on a LyapunovKrasovskii functional and stochastic analysis approach, delay-probability-distribution-dependent stability criteria have been derived in terms of linear matrix inequalities (LMIs), which can be checked easily by the LMI control toolbox. Finally two numerical examples are given to illustrate the effectiveness of the theoretical results.tr_TR
dc.description.indexTrdizintr_TR
dc.identifier.endpage1309tr_TR
dc.identifier.issn/e-issn2618-6470
dc.identifier.issue2tr_TR
dc.identifier.startpage1285tr_TR
dc.identifier.urihttps://doi.org/10.31801/cfsuasmas.769920tr_TR
dc.identifier.urihttp://hdl.handle.net/20.500.12575/76422
dc.identifier.volume69tr_TR
dc.language.isoentr_TR
dc.publisherAnkara Üniversitesi Fen Fakültesitr_TR
dc.relation.isversionof10.31801/cfsuasmas.769920tr_TR
dc.relation.journalCommunications Faculty of Sciences University of Ankara Series A1 Mathematics and Statisticstr_TR
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Başka Kurum Yazarıtr_TR
dc.subjectHopfield neural networkstr_TR
dc.subjectLinear matrix inequalitytr_TR
dc.subjectStochastic systemtr_TR
dc.titleRobust stability analysis for fuzzy stochastic Hopfield neural networks with time–varying delaystr_TR
dc.typeArticletr_TR

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