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dc.contributor.authorArik, Sabri
dc.date.accessioned2021-03-05T07:43:10Z
dc.date.available2021-03-05T07:43:10Z
dc.identifier.citationArik S., "Global asymptotic stability of hybrid bidirectional associative memory neural networks with time delays", PHYSICS LETTERS A, cilt.351, ss.85-91, 2006
dc.identifier.issn0375-9601
dc.identifier.othervv_1032021
dc.identifier.otherav_95400ecf-0639-45f0-9031-82bc889cc0c6
dc.identifier.urihttp://hdl.handle.net/20.500.12627/100491
dc.identifier.urihttps://doi.org/10.1016/j.physleta.2005.10.059
dc.description.abstractThis Letter presents a sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with distributed time delays. The results impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all bounded continuous non-monotonic neuron activation functions. The results are also compared with the previous results derived in the literature. (c) 2005 Elsevier B.V. All rights reserved.
dc.language.isoeng
dc.subjectFizik
dc.subjectTemel Bilimler
dc.subjectFİZİK, MULTİDİSİPLİNER
dc.subjectDisiplinlerarası Fizik ve İlgili Bilim ve Teknoloji Alanları
dc.subjectTemel Bilimler (SCI)
dc.titleGlobal asymptotic stability of hybrid bidirectional associative memory neural networks with time delays
dc.typeMakale
dc.relation.journalPHYSICS LETTERS A
dc.contributor.departmentİstanbul Üniversitesi , Mühendislik Fakültesi , Bilgisayar Mühendisliği
dc.identifier.volume351
dc.identifier.startpage85
dc.identifier.endpage91
dc.contributor.firstauthorID57508


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