Global Exponential Stability of a Kind of Neural Networks with Impulse and Time-Varying Delays

Author

Pu Xing-cheng ; Sun Kai

Author_Institution

Inst. of Appl. Math., Chongqing Univ. of Posts & Telecommun., Chongqing, China

fYear

2009

fDate

24-26 Sept. 2009

Firstpage

1

Lastpage

4

Abstract

In this paper, global exponential stability of a kind of impulse neural network with time-varying delays at the equilibrium points is investigated. Employing theories of the Lyapunov-Krasovskii stability theorem, Dini time differential, linear matrix inequality, differential inequality, two sufficient conditions are derived to determine the global exponential stability of this kind of impulse neural networks with time-varying delays at the equilibrium points under the assumption of activation functions only satisfying Lipschitz´s condition, improved and extended some existing results.

Keywords

Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; time-varying systems; Dini time differential; Lipschitz´s condition; Lyapunov-Krasovskii stability theorem; differential inequality; global exponential stability; impulse delay; impulse neural network; linear matrix inequality; time-varying delay; Computer networks; Delay effects; Electronic mail; Gold; Linear matrix inequalities; Mathematics; Neural networks; Stability; Sufficient conditions; Telecommunication computing;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5th International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-3692-7

Electronic_ISBN

978-1-4244-3693-4

Type

conf

DOI

10.1109/WICOM.2009.5303262

Filename

5303262