Robust stability analysis of a class of neural networks with discrete time delays
Yükleniyor...
Dosyalar
Tarih
2012-05
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pergamon-Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper studies the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete constant time delays under parameter uncertainties. The class of the neural network considered in this paper employs the activation functions which are assumed to be continuous and slope-bounded but not required to be bounded or differentiable. We conduct a stability analysis by exploiting the stability theory of Lyapunov functionals and the theory of Homomorphic mapping to derive some easily verifiable sufficient conditions for existence, uniqueness and global asymptotic stability of the equilibrium point. The conditions obtained mainly establish some time-independent relationships between the network parameters of the neural network. We make a detailed comparison between our results and the previously published corresponding results. This comparison proves that our results are new and improve and generalize the results derived in the past literature. We also give some illustrative numerical examples to show the effectiveness and applicability of our proposed stability results.
Açıklama
Anahtar Kelimeler
Computer Science, Neurosciences & Neurology, Neural networks, Delayed systems, Lyapunov functionals, Stability analysis, Varying delays, Distributed delays
Kaynak
Neural Networks
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
29-30
Sayı
Künye
Faydasıçok, Ö. & Arik, S. (2012). Robust stability analysis of a class of neural networks with discrete time delays. Neural Networks, 29-30, 52-59. doi:10.1016/j.neunet.2012.02.001
