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dc.contributor.authorOzcan, Neyir
dc.date.accessioned2021-03-03T13:22:05Z
dc.date.available2021-03-03T13:22:05Z
dc.date.issued2011
dc.identifier.citationOzcan N., "A New Sufficient Condition for Global Robust Stability of Delayed Neural Networks", NEURAL PROCESSING LETTERS, cilt.34, sa.3, ss.305-316, 2011
dc.identifier.issn1370-4621
dc.identifier.otherav_339cfe21-91c6-4229-a798-6494bbf1ec9b
dc.identifier.othervv_1032021
dc.identifier.urihttp://hdl.handle.net/20.500.12627/38946
dc.identifier.urihttps://doi.org/10.1007/s11063-011-9194-9
dc.description.abstractIn this paper, by using Lyapunov stability theorems, we present a new sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for delayed neural networks. This condition basically establishes a relationship between the network parameters of the neural system. The obtained condition can be easily verified as it is in terms of the network parameters only. Some illustrative numerical examples are also given to compare our result with the previous robust stability results derived in the literature.
dc.language.isoeng
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectAlgoritmalar
dc.subjectBİLGİSAYAR BİLİMİ, YAPAY ZEKA
dc.subjectBilgisayar Bilimi
dc.subjectBilgisayar Bilimleri
dc.subjectMühendislik ve Teknoloji
dc.titleA New Sufficient Condition for Global Robust Stability of Delayed Neural Networks
dc.typeMakale
dc.relation.journalNEURAL PROCESSING LETTERS
dc.contributor.department, ,
dc.identifier.volume34
dc.identifier.issue3
dc.identifier.startpage305
dc.identifier.endpage316
dc.contributor.firstauthorID202492


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