New global robust stability condition for uncertain neural networks with time delays
Yükleniyor...
Dosyalar
Tarih
2014-10-22
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Science BV
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, we investigate the robust stability problem for the class of delayed neural networks under parameter uncertainties and with respect to nondecreasing activation functions. Firstly, some new upper bound values for the elements of the intervalized connection matrices are obtained. Then, a new sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for this class of neural networks is derived by constructing an appropriate Lyapunov-Krasovskii functional and employing homeomorphism mapping theorem. The obtained result establishes a new relationship between the network parameters of the neural system and it is independent of the delay parameters. A comparative numerical example is also given to show the effectiveness, advantages and less conservatism of the proposed result.
Açıklama
Anahtar Kelimeler
Delayed neural networks, Lyapunov functionals, Stability analysis, Matrix analysis, Varying delays, Exponential stability, Criteria, Matrices, Norm
Kaynak
Neurocomputing
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
142
Sayı
SI
Künye
Özcan, N. & Arık, S. (2014). New global robust stability condition for uncertain neural networks with time delays. Neurocomputing, 142, 267-274. doi:10.1016/j.neucom.2014.04.040
