Title :
Globally exponential stability of a class of impulsive neural networks with variable delays
Author :
Yang, Jianfu ; Yang, Fengjian ; Zhang, Chaolong ; Wu, Dongqing ; Gao, Chuanxiang
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 Young inequality and Halanay differential inequality with delay, the sufficient conditions for globally exponential stability of neural networks are obtained.
Keywords :
Lyapunov methods; asymptotic stability; delays; neurocontrollers; time-varying systems; Halanay differential inequality; Young inequality; global Lipschitz conditions; globally exponential stability; impulsive neural networks; time-varying delays; variable delays; vector Lyapunov function; Asymptotic stability; Cellular neural networks; Chaos; Computer networks; Delay effects; Neural networks; Neurons; Robust stability; Stability criteria; Sufficient conditions; Globally exponential stability; Impulse; Lyapunov function; Neural networks; Time-varying delays;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5194641
