Asymptotic moment estimation for stochastic Lotka-Volterra model driven byG-Brownian motion

被引:1
|
作者
He, Ping [1 ,2 ]
Ren, Yong [1 ]
Zhang, Defei [2 ]
机构
[1] Anhui Normal Univ, Sch Math, Wuhu, Peoples R China
[2] Honghe Univ, Sch Math, Mengzi, Peoples R China
关键词
Lotka-Volterra model; G-Brownian motion; non-linear expectation; asymptotic moment estimation; EXPONENTIAL STABILITY; CALCULUS; THEOREM;
D O I
10.1080/17442508.2020.1784896
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A stochastic Lotka-Volterra model disturbed byG-Brownian motion (G-LVM for short) in the framework of non-linear expectation is proposed in this paper. This model takes into account the uncertainty of variance of the noise. We prove the G-LVM exists a unique solution and the solution does not tend to infinity when the time is finite under some constraints, and obtain many asymptotic moment estimations which depend on the variance ofG-Brownian motion by capacity theory, exponential martingale inequality and analytical skills.
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页码:697 / 714
页数:18
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