Convergence dynamics of stochastic reaction-diffusion neural networks with impulses and memory

被引：0
|
作者：
Peng, Jun [1 ,2 ]
Liu, Zaiming [1 ]
Zhong, Meirui [2 ]
机构：
[1] Cent S Univ, Sch Math & Stat, Changsha 410083, Hunan, Peoples R China
[2] Cent S Univ, Sch Business, Changsha 410083, Hunan, Peoples R China
来源：
NEURAL COMPUTING & APPLICATIONS | 2015年 / 26卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Stochastic system; Impulses; Memory; Reaction-diffusion; Dirichlet boundary condition; TIME-VARYING DELAYS; EXPONENTIAL STABILITY;
D O I：
10.1007/s00521-014-1745-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper deals with the problem of global stability of stochastic reaction-diffusion neural networks with impulses. The influence of diffusions, noises, delays, impulses, and Levy jumps upon the stability of the concerned system is discussed. A sufficient condition is obtained to ensure the existence, uniqueness, and exponential p-stability of the equilibrium point of the addressed stochastic reaction-diffusion neural networks with impulses by using M-matrix theory and stochastic analysis. The proposed results extend those in the earlier literature and are easier to verify.
引用
收藏
页码：651 / 657
页数：7
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