Backward doubly stochastic differential equations and SPDEs with quadratic growth

IF 1.1 2区 数学 Q3 STATISTICS & PROBABILITY
Ying Hu , Jiaqiang Wen , Jie Xiong
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引用次数: 0

Abstract

This paper shows the nonlinear stochastic Feynman–Kac formula holds under quadratic growth. For this, we initiate the study of backward doubly stochastic differential equations (BDSDEs, for short) with quadratic growth. The existence, uniqueness, and comparison theorem for one-dimensional BDSDEs are proved when the generator f(t,Y,Z) grows in Z quadratically and the terminal value is bounded, by introducing innovative approaches. Furthermore, in this framework, we utilize BDSDEs to provide a probabilistic representation of solutions to semilinear stochastic partial differential equations (SPDEs, for short) in Sobolev spaces, and use it to prove the existence and uniqueness of such SPDEs, thereby extending the nonlinear stochastic Feynman–Kac formula for linear growth introduced by Pardoux and Peng (1994).

具有二次增长的后向双随机微分方程和 SPDEs
本文证明了非线性随机费曼-卡克公式在二次增长条件下成立。为此,我们开始研究二次增长的后向双随机微分方程(简称 BDSDE)。通过引入创新方法,我们证明了当生成器 f(t,Y,Z) 在 Z 中二次增长且终值有界时,一维 BDSDE 的存在性、唯一性和比较定理。此外,在这一框架中,我们利用 BDSDE 为半线性随机偏微分方程(简称 SPDE)在 Sobolev 空间中的解提供了概率表示,并利用它证明了此类 SPDE 的存在性和唯一性,从而扩展了 Pardoux 和 Peng (1994) 引入的线性增长的非线性随机 Feynman-Kac 公式。
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
Stochastic Processes and their Applications
Stochastic Processes and their Applications 数学-统计学与概率论
CiteScore
2.90
自引率
7.10%
发文量
180
审稿时长
23.6 weeks
期刊介绍: Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests. Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.
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