Title :
Exponential stability of a class of impulsive neural networks with variable delays
Author :
Yang, Jianfu ; Yang, Fengjian ; Tao, Jicheng ; Li, Wei ; Wu, Dongqing
Author_Institution :
Dept. of Comput. Sci., Zhongkai Univ. of Agric. & Eng., Guangzhou, China
Abstract :
The main purpose of this paper is to study the globally exponential stability of the equilibrium point for a class of impulsive neural networks with time-varying delays. Without assuming global Lipschitz conditions on the activation functions, applying idea of vector Lyapunov function, combining Halanay differential inequality with delay, the sufficient conditions for globally exponential stability of neural networks are obtained.
Keywords :
Lyapunov methods; asymptotic stability; delays; neural nets; time-varying systems; Halanay differential inequality; Lipschitz condition; equilibrium point; exponential stability; impulsive neural network; time-varying delay; vector Lyapunov function; Asymptotic stability; Automation; Cellular neural networks; Delay effects; Hydrogen; Lyapunov method; Neural networks; Neurons; Stability criteria; Sufficient conditions; Globally exponential stability; Impulse; Lyapunov function; Neural networks; Time-varying delays;
Conference_Titel :
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-4794-7
Electronic_ISBN :
978-1-4244-4795-4
DOI :
10.1109/ICAL.2009.5262749
