A new upper bound for the norm of interval matrices with application to robust stability analysis of delayed neural networks

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Küçük Resim

Tarih

2013-08

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Pergamon-Elsevier Science Ltd

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Araştırma projeleri

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Dergi sayısı

Özet

The main problem with the analysis of robust stability of neural networks is to find the upper bound norm for the intervalized interconnection matrices of neural networks. In the previous literature, the major three upper bound norms for the intervalized interconnection matrices have been reported and they have been successfully applied to derive new sufficient conditions for robust stability of delayed neural networks. One of the main contributions of this paper will be the derivation of a new upper bound for the norm of the intervalized interconnection matrices of neural networks. Then, by exploiting this new upper bound norm of interval matrices and using stability theory of Lyapunov functionals and the theory of homomorphic mapping, we will obtain new sufficient conditions for the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slope-bounded activation functions. The results obtained in this paper will be shown to be new and they can be considered alternative results to previously published corresponding results. We also give some illustrative and comparative numerical examples to demonstrate the effectiveness and applicability of the proposed robust stability condition.

Açıklama

Anahtar Kelimeler

Interval matrices, Robust stability, Delayed neural networks, Lyapunov functionals, Homomorphic mapping, Discrete-time delays, Distributed delays, Exponential stability, Varying delays, Lmi approach, Neutral-type

Kaynak

Neural Networks

WoS Q Değeri

Q1

Scopus Q Değeri

Q1

Cilt

44

Sayı

Künye

Faydasıçok, Ö. & Arik, S. (2013). A new upper bound for the norm of interval matrices with application to robust stability analysis of delayed neural networks. Neural Networks, 44, 64-71. doi:10.1016/j.neunet.2013.03.014