1. Açık Erişim@BUU
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Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/28381
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dc.contributor.authorYücel, Eylem-
dc.contributor.authorArık, Sabri-
dc.date.accessioned2022-08-26T06:27:00Z-
dc.date.available2022-08-26T06:27:00Z-
dc.date.issued2015-
dc.identifier.citationNeyir, Ö. vd. (2015). "A novel condition for robust stability of delayed neural networks". Neural Information Processing, PT III, Lecture Notes in Computer Science, 273-280.en_US
dc.identifier.isbn978-3-319-26555-1-
dc.identifier.isbn978-3-319-26554-4-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://doi.org/10.1007/978-3-319-26555-1_31-
dc.identifier.urihttp://hdl.handle.net/11452/28381-
dc.descriptionBu çalışma, 9-12 Kasım 2015 tarihleri arasında İstanbul[Türkiye]'da düzenlenen 22. International Conference on Neural Information Processing (ICONIP)'de bildiri olarak sunulmuştur.tr_TR
dc.description.abstractThis paper presents a novel sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of delayed neural networks by using the Homomorphic mapping and the Lyapunov stability theorems. An important feature of the obtained result is its low computational complexity as the reported result can be verified by checking some well-known properties of some certain classes of matrices, which simplify the verification of the derived result.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectComputer scienceen_US
dc.subjectLyapunov functionalen_US
dc.subjectNeural networksen_US
dc.subjectStability analysisen_US
dc.subjectAsymptotic stabilityen_US
dc.subjectInformation scienceen_US
dc.subjectLyapunov functionsen_US
dc.subjectRobustness (control systems)en_US
dc.subjectStabilityen_US
dc.subjectDelayed neural networksen_US
dc.subjectEquilibrium pointen_US
dc.subjectGlobal robust asymptotic stabilitiesen_US
dc.subjectImportant featuresen_US
dc.subjectLow computational complexityen_US
dc.subjectLyapunov functionalsen_US
dc.subjectLyapunov stability theoremen_US
dc.subjectComplex networksen_US
dc.titleA novel condition for robust stability of delayed neural networksen_US
dc.typeProceedings Paperen_US
dc.identifier.wos000371579800031tr_TR
dc.identifier.scopus2-s2.0-84958542309tr_TR
dc.relation.publicationcategoryKonferans Öğesi - Uluslararasıtr_TR
dc.contributor.departmentUludağ Üniversitesi/Mühendislik Fakültesi/Elektrik-Elektronik Mühendisliği Bölümü.tr_TR
dc.identifier.startpage273tr_TR
dc.identifier.endpage280tr_TR
dc.identifier.volume9491tr_TR
dc.relation.journalNeural Information Processing, PT IIIen_US
dc.contributor.buuauthorÖzcan, Neyir-
dc.relation.collaborationYurt içitr_TR
dc.subject.wosComputer science, artificial intelligenceen_US
dc.subject.wosComputer science, theory & methodsen_US
dc.indexed.wosCPCISen_US
dc.indexed.scopusScopusen_US
dc.contributor.scopusid7003726676tr_TR
dc.subject.scopusBAM Neural Network; Time Lag; Bidirectional Associative Memoryen_US
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