p-th moment exponential convergence analysis for stochastic networked systems driven by fractional Brownian motion

被引:1
作者
Shi, Jiaxin [1 ]
Wu, Huaiqin [1 ]
机构
[1] Yanshan Univ, Sch Sci, Qinhuangdao 066000, Peoples R China
关键词
Stochastic Hopfield neural networks; Mild solution; Fractional Brownian motion; p-th moment exponential convergence; DIFFERENTIAL-EQUATIONS DRIVEN; DELAYED NEURAL-NETWORKS; ACTIVATION FUNCTIONS; GLOBAL CONVERGENCE; STABILITY; UNIQUENESS; EXISTENCE; TIME; CALCULUS;
D O I
10.1007/s40747-017-0049-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, the existence, uniqueness and asymptotic behavior of mild solutions of stochastic neural network systems driven by fractional Brownian motion are investigated. By applying the Banach fixed point theorem, the existence and uniqueness of mild solution are analytically proved in a Hilbert space. Based on the moment inequality of wick-type integral analysis technique, the p-th moment exponential convergence condition of the mild solution is presented. Finally, two numerical examples are presented to demonstrate the validity of the theoretical results.
引用
收藏
页码:19 / 29
页数:11
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