分数后向随机偏微分方程及其在由勒维过程驱动的部分观测系统的随机优化控制中的应用

Yuyang Ye, Yunzhang Li, Shanjian Tang
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引用次数: 0

摘要

本文研究了涉及分数拉普拉斯算子的后向随机偏微分方程(BSPDEs)的Cauchy问题。首先,利用马丁格尔表示定理和分数热核,构建了具有空间不变系数的分数BSPDEs解的显式,从而证明了强解的存在性和唯一性。然后,利用冻结系数法和延续法,我们为系数依赖于时空变量的一般分数 BSPDE 建立了 "老 "估计和好求解性。作为应用,我们利用分数邻接 BSPDEst 来研究由 $\alpha$ 稳定 L\'evy 过程驱动的部分观测系统的弹性最优控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fractional Backward Stochastic Partial Differential Equations with Applications to Stochastic Optimal Control of Partially Observed Systems driven by Lévy Processes
In this paper, we study the Cauchy problem for backward stochastic partial differential equations (BSPDEs) involving fractional Laplacian operator. Firstly, by employing the martingale representation theorem and the fractional heat kernel, we construct an explicit form of the solution for fractional BSPDEs with space invariant coefficients, thereby demonstrating the existence and uniqueness of strong solution. Then utilizing the freezing coefficients method as well as the continuation method, we establish H\"older estimates and well-posedness for general fractional BSPDEs with coefficients dependent on space-time variables. As an application, we use the fractional adjoint BSPDEs to investigate stochastic optimal control of the partially observed systems driven by $\alpha$-stable L\'evy processes.
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