New criteria for global robust stability of delayed neural networks with norm-bounded uncertainties

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dc.authorid0000-0002-4390-5139
dc.contributor.authorArık, Sabrien_US
dc.date.accessioned2015-01-15T23:02:51Z
dc.date.available2015-01-15T23:02:51Z
dc.date.issued2014-06
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.description.abstractIn this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness, and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slope-bounded activation functions. An important aspect of our results is their low computational complexity, as the reported results can be verified by checking some properties of symmetric matrices associated with the uncertainty sets of the network parameters. The obtained results are shown to be generalizations of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationArık, S. (2014). New criteria for global robust stability of delayed neural networks with norm-bounded uncertainties. IEEE Transactions on Neural Networks and Learning Systems, 25(6), 1045-1052. doi:10.1109/TNNLS.2013.2287279en_US
dc.identifier.doi10.1109/TNNLS.2013.2287279
dc.identifier.endpage1052
dc.identifier.issn2162-237X
dc.identifier.issn2162-2388
dc.identifier.issue6
dc.identifier.scopus2-s2.0-84901438357
dc.identifier.scopusqualityQ1
dc.identifier.startpage1045
dc.identifier.urihttps://hdl.handle.net/11729/532
dc.identifier.urihttp://dx.doi.org/10.1109/TNNLS.2013.2287279
dc.identifier.volume25
dc.identifier.wosWOS:000336917000003
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorArık, Sabrien_US
dc.institutionauthorid0000-0002-4390-5139
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherIEEE-INST Electrical Electronics Engineers Incen_US
dc.relation.journalIEEE Transactions on Neural Networks and Learning Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDelayed neural networksen_US
dc.subjectHomeomorphic mappingen_US
dc.subjectInterval matricesen_US
dc.subjectLyapunov functionalsen_US
dc.subjectRobust stabilityen_US
dc.subjectDiscrete-time delaysen_US
dc.subjectExponential stabilityen_US
dc.subjectVarying delaysen_US
dc.titleNew criteria for global robust stability of delayed neural networks with norm-bounded uncertaintiesen_US
dc.typeArticleen_US
dspace.entity.typePublication

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