Title :
Globally Exponential Stability of Neural Networks with Impulses and Distributed Delays
Author :
Yang, Jianfu ; Liu, Ren ; Yang, Fengjian ; Li, Wei ; Wu, Dongqing
Author_Institution :
Dept. of Comput. Sci., Zhongkai Univ. of Agric. & Eng., Guangzhou, China
Abstract :
In this paper, the main purpose is to study the global exponential stability of the equilibrium point for a class of cellular neural networks with impulses and distributed delays. With the assumption of global Lipschitz conditions on the activation function, applying idea of vector Lyapunov function, combining Halanay differential inequality with delay, a sufficient condition for globally exponential stability of neural networks is obtained.
Keywords :
Lyapunov methods; asymptotic stability; delays; neural nets; transfer functions; Halanay differential inequality; Lyapunov function; activation function; global Lipschitz conditions; neural network distributed delays; neural network globally exponential stability; neural network impulses; Agricultural engineering; Agriculture; Asymptotic stability; Cellular neural networks; Computer networks; Distributed computing; Genetics; Kernel; Lyapunov method; Neural networks; global exponential stability;
Conference_Titel :
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-0-7695-3899-0
DOI :
10.1109/WGEC.2009.33
