Further analysis of stability of uncertain neural networks with multiple time delays

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Tarih

2014-01-27

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Springer International Publishing AG

Erişim Hakkı

info:eu-repo/semantics/openAccess

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Özet

This paper studies the robust stability of uncertain neural networks with multiple time delays with respect to the class of nondecreasing activation functions. By using the Lyapunov functional and homeomorphism mapping theorems, we derive a new delay-independent sufficient condition the existence, uniqueness, and global asymptotic stability of the equilibrium point for delayed neural networks with uncertain network parameters. The condition obtained for the robust stability establishes a matrix-norm relationship between the network parameters of the neural system, and therefore it can easily be verified. We also present some constructive numerical examples to compare the proposed result with results in the previously published corresponding literature. These comparative examples show that our new condition can be considered as an alternative result to the previous corresponding literature results as it defines a new set of network parameters ensuring the robust stability of delayed neural networks.

Açıklama

Anahtar Kelimeler

Stability analysis, Delayed neural networks, Interval matrices, Lyapunov functionals, Robust exponential stability, Varying delays, Leakage terms, Dissipativity analysis, Criteria

Kaynak

Advances in Difference Equations

WoS Q Değeri

Q1

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Q2

Cilt

2014

Sayı

1

Künye

Arik, S. (2014). Further analysis of stability of uncertain neural networks with multiple time delays. Advances in Difference Equations, 2014(1), 1-16. doi:10.1186/1687-1847-2014-41