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Global asymptotic stability of a class of neural networks with time varying delays

dc.contributor.authorArik, S
dc.contributor.authorEnsari, T
dc.contributor.authorTavsanoglu, V
dc.date.accessioned2021-03-02T22:31:43Z
dc.date.available2021-03-02T22:31:43Z
dc.identifier.citationEnsari T., Arik S., Tavsanoglu V., "Global asymptotic stability of a class of neural networks with time varying delays", IEEE International Symposium on Circuits and Systems, Vancouver, Kanada, 23 - 26 Mayıs 2004, ss.820-823
dc.identifier.othervv_1032021
dc.identifier.otherav_0d35d189-5baa-4d50-ac78-8d5bddb2f4d0
dc.identifier.urihttp://hdl.handle.net/20.500.12627/14492
dc.description.abstractThis paper presents a new sufficient condition for the uniqueness and global asymptotic stability (GAS) of the equilibrium point for a larger class of neural networks with time varying delays. It is shown that the use of a more general type of Lyapunov-Krasovskii functional leads to establish global asymptotic stability of a larger class of delayed neural networks than the neural network model considered in some previous papers.
dc.language.isoeng
dc.subjectBilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği
dc.subjectSinyal İşleme
dc.subjectBilgisayar Bilimleri
dc.subjectAlgoritmalar
dc.subjectMühendislik ve Teknoloji
dc.subjectMÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK
dc.subjectMühendislik
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectBilgisayar Bilimi
dc.subjectBİLGİSAYAR BİLİMİ, YAPAY ZEKA
dc.titleGlobal asymptotic stability of a class of neural networks with time varying delays
dc.typeBildiri
dc.contributor.department, ,
dc.contributor.firstauthorID81495


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