首页> 外文期刊>The Annals of applied probability: an official journal of the Institute of Mathematical Statistics >BACKWARD STOCHASTIC DIFFERENTIAL EQUATION DRIVEN BY A MARKED POINT PROCESS: AN ELEMENTARY APPROACH WITH AN APPLICATION TO OPTIMAL CONTROL
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BACKWARD STOCHASTIC DIFFERENTIAL EQUATION DRIVEN BY A MARKED POINT PROCESS: AN ELEMENTARY APPROACH WITH AN APPLICATION TO OPTIMAL CONTROL

机译:标记点过程驱动的倒向随机微分方程:一种基本方法及其在最优控制中的应用

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摘要

We address a class of backward stochastic differential equations on a bounded interval, where the driving noise is a marked, or multivariate, point process. Assuming that the jump times are totally inaccessible and a technical condition holds (see Assumption (A) below), we prove existence and uniqueness results under Lipschitz conditions on the coefficients. Some counter-examples show that our assumptions are indeed needed. We use a novel approach that allows reduction to a (finite or infinite) system of deterministic differential equations, thus avoiding the use of martingale representation theorems and allowing potential use of standard numerical methods. Finally, we apply the main results to solve an optimal control problem for a marked point process, formulated in a classical way.
机译:我们在有界区间上处理一类后向随机微分方程,其中驱动噪声是一个标记的或多变量的点过程。假设完全无法获得跳跃时间并且保持了技术条件(请参见下面的假设(A)),我们证明在Lipschitz条件下系数的存在性和唯一性结果。一些反例表明确实需要我们的假设。我们使用一种新颖的方法,该方法可以简化为确定性微分方程的(有限或无限)系统,从而避免使用of表示法,并可能使用标准数值方法。最后,我们将主要结果应用于以经典方式制定的标记点过程的最优控制问题。

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