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

fYear

2009

fDate

5-7 Aug. 2009

Firstpage

1370

Lastpage

1373

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;

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.2009.5262749

Filename

5262749