Robust stability analysis of a class of neural networks with discrete time delays

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dc.authorid0000-0002-7621-4350
dc.authorid0000-0002-4390-5139
dc.contributor.authorFaydasıçok, Özlemen_US
dc.contributor.authorArik, Sabrien_US
dc.date.accessioned2015-01-15T23:02:04Z
dc.date.available2015-01-15T23:02:04Z
dc.date.issued2012-05
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.description.abstractThis paper studies the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete constant time delays under parameter uncertainties. The class of the neural network considered in this paper employs the activation functions which are assumed to be continuous and slope-bounded but not required to be bounded or differentiable. We conduct a stability analysis by exploiting the stability theory of Lyapunov functionals and the theory of Homomorphic mapping to derive some easily verifiable sufficient conditions for existence, uniqueness and global asymptotic stability of the equilibrium point. The conditions obtained mainly establish some time-independent relationships between the network parameters of the neural network. We make a detailed comparison between our results and the previously published corresponding results. This comparison proves that our results are new and improve and generalize the results derived in the past literature. We also give some illustrative numerical examples to show the effectiveness and applicability of our proposed stability results.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationFaydasıçok, Ö. & Arik, S. (2012). Robust stability analysis of a class of neural networks with discrete time delays. Neural Networks, 29-30, 52-59. doi:10.1016/j.neunet.2012.02.001en_US
dc.identifier.doi10.1016/j.neunet.2012.02.001
dc.identifier.endpage59
dc.identifier.issn0893-6080
dc.identifier.pmid22387479
dc.identifier.scopus2-s2.0-84860321993
dc.identifier.scopusqualityQ1
dc.identifier.startpage52
dc.identifier.urihttps://hdl.handle.net/11729/444
dc.identifier.urihttp://dx.doi.org/10.1016/j.neunet.2012.02.001
dc.identifier.volume29-30
dc.identifier.wosWOS:000304239600007
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_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.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofNeural Networksen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectComputer Scienceen_US
dc.subjectNeurosciences & Neurologyen_US
dc.subjectNeural networksen_US
dc.subjectDelayed systemsen_US
dc.subjectLyapunov functionalsen_US
dc.subjectStability analysisen_US
dc.subjectVarying delaysen_US
dc.subjectDistributed delaysen_US
dc.titleRobust stability analysis of a class of neural networks with discrete time delaysen_US
dc.typeArticleen_US
dspace.entity.typePublication

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