Globally Exponential Stability for Delayed Neural Networks Under Impulsive Control

Authors:
Cheng Hu;Haijun Jiang;Zhidong Teng
Affiliations:
College of Mathematics and System Sciences, Xinjiang University, Urumqi, People's Republic of China 830046;College of Mathematics and System Sciences, Xinjiang University, Urumqi, People's Republic of China 830046;College of Mathematics and System Sciences, Xinjiang University, Urumqi, People's Republic of China 830046
Venue:
Neural Processing Letters
Year:
2010

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Abstract

In this paper, the dynamic behaviors of a class of neural networks with time-varying delays are investigated. Some less weak sufficient conditions based on p-norm and 驴-norm are obtained to guarantee the existence, uniqueness of the equilibrium point for the addressed neural networks without impulsive control by applying homeomorphism theory. And then, by utilizing inequality technique, Lyapunov functional method and the analysis method, some new and useful criteria of the globally exponential stability with respect to the equilibrium point under impulsive control we assumed are derived based on p-norm and 驴-norm, respectively. Finally, an example with simulation is given to show the effectiveness of the obtained results.