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一类Lévy噪声驱动倒向随机偏微分方程的随机最大值原理
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作者 贾秀利 关丽红 闫龙 《吉林大学学报(理学版)》 CAS CSCD 北大核心 2015年第3期467-470,共4页
利用凸变分法和对偶技术,研究一类Lévy噪声驱动的倒向随机发展型偏微分方程的最优控制问题,得到了该问题的随机最大值原理.
关键词 Lévy噪声 倒向随机偏微分方程 随机最大值原理
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一类部分信息的随机控制问题的极值原理(英文)
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作者 冉启康 《应用数学》 CSCD 北大核心 2009年第2期421-429,共9页
在本文中,我们证明了一类部分信息的随机控制问题的极值原理的一个充分条件和一个必要条件.其中,随机控制问题的控制系统是一个由鞅和Brown运动趋动的随机偏微分方程.
关键词 倒向随机偏微分方程 跳时间 随机最优控制问题 部分信息
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Backward Doubly Stochastic Differential Equations with Jumps and Stochastic Partial Differential-Integral Equations 被引量:5
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作者 Qingfeng ZHU Yufeng SHI 《Chinese Annals of Mathematics,Series B》 SCIE CSCD 2012年第1期127-142,共16页
Backward doubly stochastic differential equations driven by Brownian motions and Poisson process (BDSDEP) with non-Lipschitz coefficients on random time interval are studied. The probabilistic interpretation for the... Backward doubly stochastic differential equations driven by Brownian motions and Poisson process (BDSDEP) with non-Lipschitz coefficients on random time interval are studied. The probabilistic interpretation for the solutions to a class of quasilinear stochastic partial differential-integral equations (SPDIEs) is treated with BDSDEP. Under non-Lipschitz conditions, the existence and uniqueness results for measurable solutions to BDSDEP are established via the smoothing technique. Then, the continuous depen- dence for solutions to BDSDEP is derived. Finally, the probabilistic interpretation for the solutions to a class of quasilinear SPDIEs is given. 展开更多
关键词 Backward doubly stochastic differential equations Stochastic partialdifferential-integral equations Random measure Poisson process
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FOUR STEP SCHEME FOR GENERAL MARKOVIAN FORWARD-BACKWARD SDES 被引量:1
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作者 Jin MA Jiongmin YONG Yanhong ZHAO 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2010年第3期546-571,共26页
This paper studies a class of forward-backward stochastic differential equations (FBSDE)in a general Markovian framework.The forward SDE represents a large class of strong Markov semimartingales,and the backward gener... This paper studies a class of forward-backward stochastic differential equations (FBSDE)in a general Markovian framework.The forward SDE represents a large class of strong Markov semimartingales,and the backward generator requires only mild regularity assumptions.The authors showthat the Four Step Scheme introduced by Ma,et al.(1994) is still effective in this case.Namely,the authors show that the adapted solution of the FBSDE exists and is unique over any prescribedtime duration;and the backward components can be determined explicitly by the forward componentvia the classical solution to a system of parabolic integro-partial differential equations.An importantconsequence the authors would like to draw from this fact is that,contrary to the general belief,in aMarkovian set-up the martingale representation theorem is no longer the reason for the well-posednessof the FBSDE,but rather a consequence of the existence of the solution of the decoupling integralpartialdifferential equation.Finally,the authors briefly discuss the possibility of reducing the regularityrequirements of the coefficients by using a scheme proposed by F.Delarue (2002) to the current case. 展开更多
关键词 Forward-backward stochastic differential equations Four Step Scheme parabolic integropartial differential equation strong Markov semi-martingales.
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BSDE,path-dependent PDE and nonlinear Feynman-Kac formula 被引量:9
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作者 PENG ShiGe WANG FaLei 《Science China Mathematics》 SCIE CSCD 2016年第1期19-36,共18页
We introduce a new type of path-dependent quasi-linear parabolic PDEs in which the continuous paths on an interval [0, t] become the basic variables in the place of classical variables (t, x) ∈[0, T]× R^d. Thi... We introduce a new type of path-dependent quasi-linear parabolic PDEs in which the continuous paths on an interval [0, t] become the basic variables in the place of classical variables (t, x) ∈[0, T]× R^d. This new type of PDEs are formulated through a classical BSDE in which the terminal values and the generators are allowed to be general function of Brownian motion paths. In this way, we establish the nonlinear Feynman- Kac formula for a general non-Markoviau BSDE. Some main properties of solutions of this new PDEs are also obtained. 展开更多
关键词 backward stochastic differential equation nonlinear Feynman-Kac formula path-dependent PDE
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