New criteria for global robust stability of delayed neural networks with norm-bounded uncertainties
Yükleniyor...
Dosyalar
Tarih
2014-06
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE-INST Electrical Electronics Engineers Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring 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. An important aspect of our results is their low computational complexity, as the reported results can be verified by checking some properties of symmetric matrices associated with the uncertainty sets of the network parameters. The obtained results are shown to be generalizations of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.
Açıklama
Anahtar Kelimeler
Delayed neural networks, Homeomorphic mapping, Interval matrices, Lyapunov functionals, Robust stability, Discrete-time delays, Exponential stability, Varying delays
Kaynak
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
25
Sayı
6
Künye
Arık, S. (2014). New criteria for global robust stability of delayed neural networks with norm-bounded uncertainties. IEEE Transactions on Neural Networks and Learning Systems, 25(6), 1045-1052. doi:10.1109/TNNLS.2013.2287279
