New global robust stability condition for uncertain neural networks with time delays

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Tarih

2014-10-22

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Elsevier Science BV

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Araştırma projeleri

Organizasyon Birimleri

Dergi sayısı

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
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