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arXiv 2109.11461math.PR
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关于分数阶倒向随机微分方程的若干结果

Some Results on Backward Stochastic Differential Equations of Fractional Order

Nazim I. Mahmudov, Arzu Ahmadova

摘要:

本文研究了分数阶随机微分方程,即Caputo型分数阶倒向随机微分方程(Caputo fBSDEs,简称Caputo fBSDEs),研究了系数满足利普希茨条件的$α\in (\frac{1}{2},1)$阶Caputo fBSDEs适应解的适定性.本文的一个创新之处是在平方可积〔的〕可测函数空间中引入了一个新的加权范数,这对于证明一个基本引理及其适定性是有用的。对于这类系统,我们然后显示随机Volterra积分方程的概念和温和的解决方案之间的一致性。

英文摘要:

In this article, we deal with fractional stochastic differential equations, so-called Caputo type fractional backward stochastic differential equations (Caputo fBSDEs, for short), and study the well-posedness of an adapted solution to Caputo fBSDEs of order $α\in (\frac{1}{2},1)$ whose coefficients satisfy a Lipschitz condition. A novelty of the article is that we introduce a new weighted norm in the square integrable measurable function space that is useful for proving a fundamental lemma and its well-posedness. For this class of systems, we then show the coincidence between the notion of stochastic Volterra integral equation and the mild solution.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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