Data informed solution estimation for forward-backward stochastic differential equations

IF 2 2区 数学 Q1 MATHEMATICS
F. Bao, Yanzhao Cao, J. Yong
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引用次数: 3

Abstract

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.
前向-后向随机微分方程的数据知情解估计
将前向-后向随机微分方程(FBSDE)系统引入抛物型偏微分方程的概率描述中。尽管FBSDE系统的概率行为使其在许多应用中成为一个自然的数学模型,但系统中包含的随机积分在解中产生了不确定性,这使得解估计成为一项具有挑战性的任务。在本文中,我们假设我们可以接收到解的部分噪声观测,并引入一种最优滤波方法来对FBSDE进行基于数据的解估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.90
自引率
4.50%
发文量
29
审稿时长
>12 weeks
期刊介绍: Analysis and Applications publishes high quality mathematical papers that treat those parts of analysis which have direct or potential applications to the physical and biological sciences and engineering. Some of the topics from analysis include approximation theory, asymptotic analysis, calculus of variations, integral equations, integral transforms, ordinary and partial differential equations, delay differential equations, and perturbation methods. The primary aim of the journal is to encourage the development of new techniques and results in applied analysis.
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