New global robust stability condition for uncertain neural networks with time delays

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dc.authorid0000-0002-4390-5139
dc.contributor.authorÖzcan, Neyiren_US
dc.contributor.authorArik, Sabrien_US
dc.date.accessioned2015-07-14T10:59:32Z
dc.date.available2015-07-14T10:59:32Z
dc.date.issued2014-10-22
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 investigate the robust stability problem for the class of delayed neural networks under parameter uncertainties and with respect to nondecreasing activation functions. Firstly, some new upper bound values for the elements of the intervalized connection matrices are obtained. Then, a new sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for this class of neural networks is derived by constructing an appropriate Lyapunov-Krasovskii functional and employing homeomorphism mapping theorem. The obtained result establishes a new relationship between the network parameters of the neural system and it is independent of the delay parameters. A comparative numerical example is also given to show the effectiveness, advantages and less conservatism of the proposed result.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationÖzcan, N. & Arık, S. (2014). New global robust stability condition for uncertain neural networks with time delays. Neurocomputing, 142, 267-274. doi:10.1016/j.neucom.2014.04.040en_US
dc.identifier.doi10.1016/j.neucom.2014.04.040
dc.identifier.endpage274
dc.identifier.issn0925-2312
dc.identifier.issn1872-8286
dc.identifier.issueSI
dc.identifier.scopus2-s2.0-84904368277
dc.identifier.scopusqualityQ1
dc.identifier.startpage267
dc.identifier.urihttps://hdl.handle.net/11729/565
dc.identifier.urihttp://dx.doi.org/10.1016/j.neucom.2014.04.040
dc.identifier.volume142
dc.identifier.wosWOS:000340341400028
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorArik, Sabrien_US
dc.institutionauthorid0000-0002-4390-5139
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherElsevier Science BVen_US
dc.relation.ispartofNeurocomputingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDelayed neural networksen_US
dc.subjectLyapunov functionalsen_US
dc.subjectStability analysisen_US
dc.subjectMatrix analysisen_US
dc.subjectVarying delaysen_US
dc.subjectExponential stabilityen_US
dc.subjectCriteriaen_US
dc.subjectMatricesen_US
dc.subjectNormen_US
dc.titleNew global robust stability condition for uncertain neural networks with time delaysen_US
dc.typeArticleen_US
dspace.entity.typePublication

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