Mean square exponential stability of stochastic nonlinear delay systems

被引:29
|
作者
Zhu, Quanxin [1 ,2 ,3 ]
Song, Shiyun [1 ,2 ]
Tang, Tianren [4 ]
机构
[1] Nanjing Normal Univ, Sch Math Sci, Nanjing, Jiangsu, Peoples R China
[2] Nanjing Normal Univ, Inst Finance & Stat, Nanjing, Jiangsu, Peoples R China
[3] Univ Bielefeld, Dept Math, Bielefeld, Germany
[4] Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Stochastic nonlinear delay system; polynomial growth condition; global Lipschitz condition; mean square globally exponential stability; stabilisation; RECURRENT NEURAL-NETWORKS; DIFFERENTIAL-EQUATIONS; NOISE SUPPRESSES; STABILIZATION; DESTABILIZATION; GROWTH;
D O I
10.1080/00207179.2016.1249030
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we are concernedwith the stability of stochastic nonlinear delay systems. Different from the previous literature, we aim to show that when the determinate nonlinear delay system is globally exponentially stable, the corresponding stochastic nonlinear delay system can be mean square globally exponentially stable. In particular, we remove the linear growth condition and introduce a new polynomial growth condition for g(x(t), x(t-tau(t))), which overcomes the limitation of application scope and the boundedness of diffusion term form. Finally, we provide an example to illustrate our results.
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页码:2384 / 2393
页数:10
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