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

fYear

2009

fDate

5-7 Aug. 2009

Firstpage

1426

Lastpage

1430

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICAL.2009.5262761

Filename

5262761