TITLE:
A New Global Asymptotic Stability Result of Delayed Neural Networks via Nonsmooth Analysis
AUTHORS:
Yaning Gu, Deyou Liu, Wenjuan Wu, Jingwen Zhang
KEYWORDS:
Delayed Neural Networks, Global Asymptotic Stability, Nonsmooth Analysis
JOURNAL NAME:
International Journal of Communications, Network and System Sciences,
Vol.3 No.3,
March
31,
2010
ABSTRACT: In the paper, we obtain new sufficient conditions ensuring existence, uniqueness, and asymptotic stability of the equilibrium point for delayed neural network via nonsmooth analysis, which makes use of the Lipschitz property of the functions. Based on this tool of nonsmooth analysis, we first obtain a couple of general results concerning the existence and uniqueness of the equilibrium point. Then we drive some new sufficient conditions ensuring global asymptotic stability of the equilibrium point. Finally, there are the illustrative examples feasibility and effectiveness of our results. Throughout our paper, the activation function is a more general function which has a wide application.