Stochastic global exponential stability of neutral-type impulsive neural networks with both Markovian Jumping and mixed time delays

Author

Yan, Gao ; Wuneng, Zhou ; Jing, Zhao ; Dongbing, Tong ; Chuan, Ji

Author_Institution

Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China

fYear

2012

fDate

25-27 July 2012

Firstpage

3244

Lastpage

3249

Abstract

The problem of stochastic global exponential stability for neural networks of neutral-type impulsive with both Markovian Jumping and mixed time delays is studied in this paper. By using stochastic analysis approach and Lyapunov-Krasovskii method, a sufficient condition under which the neural networks of neutral-type impulsive with both time delays and Markovian Jumping is obtained. To illustrate the effectiveness of the result proposed in this paper, a numerical example is given.

Keywords

Lyapunov methods; asymptotic stability; delays; neural nets; stochastic systems; Lyapunov-Krasovskii method; Markovian jumping; mixed time delays; neutral-type impulsive neural networks; stochastic analysis approach; stochastic global exponential stability; sufficient condition; Control theory; Delay effects; Neural networks; Stability analysis; Stochastic processes; Vectors; Exponential Stability; Impulsive; Markovian Jumping; Mixed Time Delays; Neutral-Type Neural Networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2012 31st Chinese

Conference_Location

Hefei

ISSN

1934-1768

Print_ISBN

978-1-4673-2581-3

Type

conf

Filename

6390481