A new condition for robust stability of uncertain neural networks with time delays
Yükleniyor...
Dosyalar
Tarih
2014-03-27
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Science BV
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper is concerned with the global asymptotic stability problem of dynamical neural networks with multiple time delays under parameter uncertainties. First carrying out an analysis of existence and uniqueness of the equilibrium point by means of the Homeomorphism theory, and then, studying the global asymptotic stability of the equilibrium point by constructing a suitable Lyapunov functional, we derive a new global robust stability criterion for the class of delayed neural networks with respect to the Lipschitz activation functions. The result obtained establishes a relationship between the neural network parameters only and it is independent of the time delay parameters. It is shown that the established stability condition generalizes some existing ones and it can be considered to an alternative result to some other corresponding results derived in previous literature. We also give some comparative numerical examples to demonstrate the validity and effectiveness of our proposed result.
Açıklama
Anahtar Kelimeler
Interval matrices, Robust stability, Delayed neural networks, Lyapunov functionals, Homeomorphic mapping, Exponential stability, Varying delays, Distributed delays, Neutral-type, Discrete, Criterion, Matrices, Norm
Kaynak
Neurocomputing
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
128
Sayı
Künye
Arık, S. (2014). A new condition for robust stability of uncertain neural networks with time delays. Neurocomputing, 128, 476-482. doi:10.1016/j.neucom.2013.08.017
