Data informed solution estimation for forward-backward stochastic differential equations
Data informed solution estimation for forward-backward stochastic differential equations
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DOI：
10.1142/s0219530520400102
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发表时间：
2020-10
影响因子：
2.2
通讯作者：
F. Bao;Yanzhao Cao;J. Yong
中科院分区：
文献类型：
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作者：
F. Bao;Yanzhao Cao;J. Yong
引入了正倒向随机微分方程系统作为抛物型偏微分方程的概率描述。虽然FBBNN系统的概率行为使其在许多应用中成为自然的数学模型，但系统中包含的随机积分在解中产生不确定性，这使得解估计成为一项具有挑战性的任务。在本文中，我们假设，我们可以收到部分噪声的意见，解决方案，并介绍了一个最佳的过滤方法，使数据知情的解决方案估计FBSDES。
Forward-backward stochastic differential equation (FBSDE) systems were introduced as a probabilistic description for parabolic type partial differential equations. Although the probabilistic behavior of the FBSDE system makes it a natural mathematical model in many applications, the stochastic integrals contained in the system generate uncertainties in the solutions which makes the solution estimation a challenging task. In this paper, we assume that we could receive partial noisy observations on the solutions and introduce an optimal filtering method to make a data informed solution estimation for FBSDEs.