Exponential Synchronization of Coupled Stochastic Memristor-Based Neural Networks With Time-Varying Probabilistic Delay Coupling and Impulsive Delay

被引:203
作者
Bao, Haibo [1 ,2 ]
Park, Ju H. [2 ]
Cao, Jinde [3 ,4 ]
机构
[1] Southwest Univ, Sch Math & Stat, Chongqing 400715, Peoples R China
[2] Yeungnam Univ, Dept Elect Engn, Nonlinear Dynam Grp, Gyongsan 38541, South Korea
[3] Southeast Univ, Dept Math, Nanjing 210096, Jiangsu, Peoples R China
[4] King Abdulaziz Univ, Dept Math, Fac Sci, Jeddah 21589, Saudi Arabia
基金
新加坡国家研究基金会; 中国国家自然科学基金;
关键词
Probabilistic time-varying delay; stochastic memristor-based neural networks; synchronization; time-varying impulsive delay; COMPLEX DYNAMICAL NETWORKS; GLOBAL SYNCHRONIZATION; STABILITY; ARRAY; BIFURCATION; SYSTEMS;
D O I
10.1109/TNNLS.2015.2475737
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 exponential synchronization of coupled stochastic memristor-based neural networks with probabilistic time-varying delay coupling and time-varying impulsive delay. There is one probabilistic transmittal delay in the delayed coupling that is translated by a Bernoulli stochastic variable satisfying a conditional probability distribution. The disturbance is described by a Wiener process. Based on Lyapunov functions, Halanay inequality, and linear matrix inequalities, sufficient conditions that depend on the probability distribution of the delay coupling and the impulsive delay were obtained. Numerical simulations are used to show the effectiveness of the theoretical results.
引用
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页码:190 / 201
页数:12
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