Global Exponential Stability of a General Class of Neural Networks with Delays and Impulses

Author

Zhang, Chaolong ; Yang, Fengjian ; Wu, Dongqing

Author_Institution

Dept. of Computational Sci., Zhongkai Univ. of Agric. & Technol., Guangzhou

Volume

1

fYear

0

fDate

0-0 0

Firstpage

2815

Lastpage

2819

Abstract

By using the methods of variation of constants in ordinary differential equations, piecewise Lyapunov function and the contraction mapping principle in Banach spaces, the exponential stability of a general class of neural networks with delays and impulses is discussed. The existence of a uniqueness of periodic solution for this model is obtained, and several global exponential stability criteria of the equilibrium point are established. Two linear impulsive neural networks with delays are constructed, which can be used to design impulsive controllers to control the exponential stability of the system. This method is possible in practical application

Keywords

Banach spaces; Lyapunov methods; asymptotic stability; control system synthesis; delays; differential equations; linear systems; neurocontrollers; transient response; Banach spaces; contraction mapping principle; delays; exponential stability; linear impulsive neural networks; ordinary differential equations; piecewise Lyapunov function; Agriculture; Chaos; Computer networks; Control systems; Differential equations; Electronic mail; Lyapunov method; Neural networks; Space technology; Stability; delays; global exponential stability; impulses; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712878

Filename

1712878