Dynamical analysis of uncertain neural networks with multiple time delays
Yükleniyor...
Dosyalar
Tarih
2016-02-17
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper investigates the robust stability problem for dynamical neural networks in the presence of time delays and norm-bounded parameter uncertainties with respect to the class of non-decreasing, non-linear activation functions. By employing the Lyapunov stability and homeomorphism mapping theorems together, a new delay-independent sufficient condition is obtained for the existence, uniqueness and global asymptotic stability of the equilibrium point for the delayed uncertain neural networks. The condition obtained for robust stability establishes a matrix-norm relationship between the network parameters of the neural system, which can be easily verified by using properties of the class of the positive definite matrices. Some constructive numerical examples are presented to show the applicability of the obtained result and its advantages over the previously published corresponding literature results.
Açıklama
Anahtar Kelimeler
Neural networks, Time delays, Robust stability, Uncertain systems, Robust exponential stability, Varying delays
Kaynak
International Journal of Systems Science
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
47
Sayı
3
Künye
Arık, S. (2016). Dynamical analysis of uncertain neural networks with multiple time delays. International Journal of Systems Science, 47(3), 730-739. doi:10.1080/00207721.2014.902158