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Global robust stability analysis of neural networks with discrete time delays

dc.contributor.authorArik, Sabri
dc.date.accessioned2021-03-05T18:46:14Z
dc.date.available2021-03-05T18:46:14Z
dc.date.issued2005
dc.identifier.citationArik S., "Global robust stability analysis of neural networks with discrete time delays", CHAOS SOLITONS & FRACTALS, cilt.26, ss.1407-1414, 2005
dc.identifier.issn0960-0779
dc.identifier.othervv_1032021
dc.identifier.otherav_cbecebdc-34ca-4b01-a567-11549da7d021
dc.identifier.urihttp://hdl.handle.net/20.500.12627/135049
dc.identifier.urihttps://doi.org/10.1016/j.chaos.2005.03.025
dc.description.abstractGlobal robust convergence properties of continuous-time neural networks with discrete delays are studied. By using a Lyapunov functional, we derive a delay independent stability condition for the existence uniqueness and global robust asymptotic stability of the equilibrium point. The condition is in terms of the network parameters only and can be easily verified. It is also shown that the obtained result improves and generalizes a previously published result. (c) 2005 Elsevier Ltd. All rights reserved.
dc.language.isoeng
dc.subjectTemel Bilimler
dc.subjectFizik
dc.subjectGenel Fizik
dc.subjectFİZİK, MATEMATİK
dc.subjectDisiplinlerarası Fizik ve İlgili Bilim ve Teknoloji Alanları
dc.subjectFİZİK, MULTİDİSİPLİNER
dc.subjectTemel Bilimler (SCI)
dc.subjectMatematik
dc.subjectMATEMATİK, İNTERDİSKÜP UYGULAMALAR
dc.titleGlobal robust stability analysis of neural networks with discrete time delays
dc.typeMakale
dc.relation.journalCHAOS SOLITONS & FRACTALS
dc.contributor.departmentİstanbul Üniversitesi , Mühendislik Fakültesi , Bilgisayar Mühendisliği
dc.identifier.volume26
dc.identifier.issue5
dc.identifier.startpage1407
dc.identifier.endpage1414
dc.contributor.firstauthorID57507


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