Further analysis of global robust stability of neural networks with multiple time delays
Yükleniyor...
Dosyalar
Tarih
2012-04
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pergamon-Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper deals with the problem of the global robust asymptotic stability of the class of dynamical neural networks with multiple time delays. We propose a new alternative sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point under parameter uncertainties of the neural system. We first prove the existence and uniqueness of the equilibrium point by using the Homomorphic mapping theorem. Then, by employing a new Lyapunov functional, the Lyapunov stability theorem is used to establish the sufficient condition for the asymptotic stability of the equilibrium point. The obtained condition is independent of time delays and relies on the network parameters of the neural system only. Therefore, the equilibrium and stability properties of the delayed neural network can be easily checked. We also make a detailed comparison between our result and the previous corresponding results derived in the previous literature. This comparison proves that our result is new and improves some of the previously reported robust stability results. Some illustrative numerical examples are given to show the applicability and advantages of our result.
Açıklama
Anahtar Kelimeler
Varying delays, Exponential stability, Distributed delays, Neutral-type, Dependent stability, Discrete, Criteria
Kaynak
Journal of The Franklin Institute-Engineering and Applied Mathematics
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
349
Sayı
3
Künye
Faydasıçok, Ö. & Arik, S. (2012). Further analysis of global robust stability of neural networks with multiple time delays. Journal of The Franklin Institute-Engineering and Applied Mathematics, 349(3), 813-825. doi:10.1016/j.jfranklin.2011.11.007
