Title :
Globally exponential stability of cellular neural networks with distributed delays and large impulses
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 cellular neural networks with distributed delays and large impulses. With 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; cellular neural nets; delays; Halanay differential inequality; activation function; cellular neural network; distributed delay; global Lipschitz condition; global exponential stability; large impulse; vector Lyapunov function; Asymptotic stability; Automation; Cellular neural networks; Computer networks; Distributed computing; Kernel; Logistics; Lyapunov method; Neural networks; Sufficient conditions; Distributed delays; Globally exponential stability; Impulse; Lyapunov function; Neural networks;
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.2009.5262761
