一类随机不动点定理及其特例

在随机拓扑度的基础上进一步研究了随机不动点问题,得到了若干新的随机不动点定理.作为特例,也给出了相应的确定性算子的边界不动点定理.     

随机非线性凝聚算子方程的随机解

利用随机拓扑度理论研究随机非线性凝聚算子,在一定条件下得到随机算子方程A（w,x）=μx的随机解和随机算子不动点的存在性,所得结论减弱了已知文献中相应定理的条件．     

随机泛函分析中的锐角原理及应用(英文)

在随机泛函分析中证明了著名的锐角原理和随机一一映射定理,并且得到了若干新的结果．     

关于三值R0命题逻辑系统的若干注记

在三值R0命题逻辑系统中证明了随机真度的MP、HS和交推理规则;提出了随机开放度,指出随机开放度与随机发散度是从两个不同的角度刻画了理论的相容程度,并得出对同一个理论而言,二者取值相等的结论.     

R0型命题逻辑系统的随机化

利用赋值集的随机化方法,在R0型n值命题逻辑系统和R0型模糊命题逻辑系统中提出了公式的随机真度和随机距离的概念,建立了随机度量空间.指出当取均匀概率时,随机真度就转化为计量逻辑学中的真度,从而建立了更一般的随机逻辑度量空间.     

关于任意非负随机序列随机和的一类随机偏差定理

本文引入任意随机变量序列随机极限对数似然比概念,作为任意相依随机序列联合分布与其边缘乘积分布“不相似”性的一种度量,利用构造新的密度函数方法来建立几乎处处收敛的上鞅,在适当的条件下,给出了任意受控随机序列的一类随机偏差定理.     

随机结构空间理论初探

提出了随机结构空间的概念，引出了随机拓扑空间、随机度量空间、随机赋范空间、随机内积空间、随机关系等随机数学结构的概念，初步研究了随机度量空间、随机赋范空间、随机内积空间的基本构造以及与概率度量空间、概率赋范空间、概率内积空间的关系。     

随机度量理论及其应用在我国最近进展的综述

本旨在全面综述随机度量理论及其应用过去十年在我国发展过程中所获得的主要结果与思想方法,本由十节组成,第一节对我们工作的背景-概率度量空间与随机度量空间理论作一简单的介绍;第二节给出某些有关随机泛函分析及取值于抽象空间的可测函数的预备知识,第三节阐明随机泛函分析与原始随机度量理论（本称之为F-随机度量理论）的整体关系,主要结果是在随机元生成空间上给出自然且合理的随机度量与随机范数的构造,从而将随机元与随机算子理论的研究纳入随机度量理论框架,主要思想是将随机泛函分析视为随机度量空间体系上的分析学而统一地发展;从而形成了发展随机泛函分析的一个新的途径-空间随机化途径;除此之外,在本节我们也从随机过程理论的观点出发首次提出对应于随机度量理论原始版本的一种新的随机共轭空间理论（叫作F-随机共轭空间理论）,它的突出优点是能保持象随机过程的样本性质这样更精细的特性（本节由作的工作构成）,在第四节,基于作最近提出的随机度量理论的一个新的版本（本称之为E-随机度量理论）,从传统泛函分析的角度对过去已被发展起来的随机共轭空间理论（本称之为E-随机共轭空间理论）的基本结果进行系统整理并给以全新的处理（本节内容整体上由作最近的一篇论构成,也尤其提到朱林户等人的重要工作）,在本节我们也以相当的篇幅论述F-随机共轭空间理论与E-随机共轭空间理论的内在关系与本质差异,在下面紧跟的两节,致力于E-随机共轭空间理论深层次的结果,尤其突出了E-随机赋范模与传统的赋范空间、E-随机共轭空间与经典共轭空间之间的内在联系;在第五节给出了几类E-随机赋范模的E-随机共轭空间的表示定理（主要由作的工作,作与游兆水及林熙合作的工作,还有巩馥州与刘清荣合作的工作组成）,在六节给出完备E-随机赋范模为随机自反的特征化定理（主要由作及合作的工作组成）,尤其是第五及第六节中,我们给出随机度量理论在随机泛函分析及经典Banach空间中若干实质性的应用;第七节简要给出E-随机赋半范模及E-随机对偶系理论初步;第八节简单阐明随机度量理论与泛函分析的关系;第九节简单阐明了随机度量理论与概率度量空间理论的关系,最后在第十节结合随机度量理论,Banach空间理论及随机泛函分析对发展随机泛函分析的空间随机化途径的合理性与优越性作了进一步的分析。     

关于随机非线性算子的若干定理

本文利用随机拓扑度研究了随机凝聚算子的随机不动点定理和随机方程A(w,x)=μx的随机解,以及随机全连续算子的固有值和固有函数,得到若干新结果．     

三值R_0命题逻辑系统中理论的随机发散度

在三值R_0命题逻辑系统中,给出了随机相似度和随机逻辑伪距离的基本性质.然后在随机逻辑度量空间中提出了理论的随机发散度,指出全体原子公式之集在随机逻辑度量空间中未必是全发散的,其是否全发散取决于给定的随机数序的分布.     

SEMI-LINEAR SYSTEMS OF BACKWARD STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS IN R~n

This paper explores the diffeomorphism of a backward stochastic ordinary differential equation (BSDE) to a system of semi-linear backward stochastic partial differential equations (BSPDEs), under the inverse of a stochastic flow generated by an ordinary stochastic differential equation (SDE). The author develops a new approach to BSPDEs and also provides some new results. The adapted solution of BSPDEs in terms of those of SDEs and BSDEs is constructed. This brings a new insight on BSPDEs, and leads to a probabilistic approach. As a consequence, the existence, uniqueness, and regularity results are obtained for the (classical, Sobolev, and distributional) solution of BSPDEs. The dimension of the space variable x is allowed to be arbitrary n, and BSPDEs are allowed to be nonlinear in both unknown variables, which implies that the BSPDEs may be nonlinear in the gradient. Due to the limitation of space, however, this paper concerns only classical solution of BSPDEs under some more restricted assumptions.     

Semi-linear degenerate backward stochastic partial differential equations and associated forward–backward stochastic differential equations

In this paper, we consider the Cauchy problem of semi-linear degenerate backward stochastic partial differential equations (BSPDEs) under general settings without technical assumptions on the coefficients. For the solution of semi-linear degenerate BSPDE, we first give a proof for its existence and uniqueness, as well as regularity. Then the connection between semi-linear degenerate BSPDEs and forward–backward stochastic differential equations (FBSDEs) is established, which can be regarded as an extension of the Feynman–Kac formula to the non-Markovian framework.     

分数布朗运动驱动下z一致连续的BSDE解的存在性与唯一性

本文研究一类由分数布朗运动驱动的一维倒向随机微分方程解的存在性与唯一性问题,在假设其生成元满足关于y Lipschitz连续,但关于z一致连续的条件下,通过应用分数布朗运动的Tanaka公式以及拟条件期望在一定条件下满足的单调性质,得到倒向随机微分方程的解的一个不等式估计,应用Gronwall不等式得到了一个关于这类方程的解的存在性与唯一性结果,推广了一些经典结果以及生成元满足一致Lipschitz条件下的由分数布朗运动驱动的倒向随机微分方程解的结果.     

A BSDE approach to Nash equilibrium payoffs for stochastic differential games with nonlinear cost functionals

In this paper, we study Nash equilibrium payoffs for two-player nonzero-sum stochastic differential games via the theory of backward stochastic differential equations. We obtain an existence theorem and a characterization theorem of Nash equilibrium payoffs for two-player nonzero-sum stochastic differential games with nonlinear cost functionals defined with the help of doubly controlled backward stochastic differential equations. Our results extend former ones by Buckdahn et al. (2004) [3] and are based on a backward stochastic differential equation approach.     

On semi-linear degenerate backward stochastic partial differential equations

 In this paper we study a class of one-dimensional, degenerate, semilinear backward stochastic partial differential equations (BSPDEs, for short) of parabolic type. By establishing some new a priori estimates for both linear and semilinear BSPDEs, we show that the regularity and uniform boundedness of the adapted solution to the semilinear BSPDE can be determined by those of the coefficients, a special feature that one usually does not expect from a stochastic differential equation. The proof follows the idea of the so-called bootstrap method, which enables us to analyze each of the derivatives of the solution under consideration. Some related results, including some comparison theorems of the adapted solutions for semilinear BSPDEs, as well as a nonlinear stochastic Feynman-Kac formula, are also given. Received: 16 January 2001 / Revised version: 11 October 2001 / Published online: 14 June 2002     

Probabilistic Solutions for a Class of Path-Dependent Hamilton-Jacobi-Bellman Equations

This article shows that the solution of a backward stochastic differential equation under G-expectation provides a probabilistic interpretation for the viscosity solution of a type of path-dependent Hamilton-Jacobi-Bellman equation. Particularly, a G-martingale can be considered as a nonlinear path-dependent partial differential equation (PDE). We also show that certain class of path-dependent PDEs can be transformed into classical multiple state-dependent PDEs. As an application, the path-dependent uncertain volatility model can be described directly by path-dependent Black-Scholes-Barrenblett equations.     

Stochastic inertial manifold

A nonlinear stochastic evolution equation in Hilbert space with generalized additive white noise is considered. A concept of stochastic mertial manifold is introduced, defined as a random manifold depending on time, which is finite dimensional, invariant for the dynamic, and attracts exponentially fast all the trajectories as t → ∞. Under the classical spectral gap condition of the deterministic theory, the existence of a stochastic inertial manifold is proved. It is obtained as the solution of a stochastic partial differential equation of degenerate parabolic type, studied by a variant of Bernstein method. A result of existence and uniqueness of a stationary inertial manifold is also proved; the stationary inertial manifold contains the random attractor, introduced in previous works.     

特殊形式的倒向随机微分方程在金融市场中的应用

首先,针对一类线性倒向随机微分方程,给出了g-鞅同鞅之间相互联系所满足的充分条件.通过该条件得到了经典的Black-Scholes模型下未定权益的公平价格过程以及最优增长投资策略的价格过程.其次,引入了带惩罚的非线性倒向随机微分方程,并通过惩罚比率的不同取值来讨论相关的经济学意义.     

Stochastic Optimal Control for the Stochastic Heat Equation with Exponentially Growing Coefficients and with Control and Noise on a Subdomain

Abstract

We consider stochastic optimal control problems in Banach spaces, related to nonlinear controlled equations with dissipative non linearities: on the nonlinear term we do not impose any growth condition. The problems are treated via the backward stochastic differential equations approach, that allows also to solve in mild sense Hamilton Jacobi Bellman equations in Banach spaces. We apply the results to controlled stochastic heat equation, in space dimension 1, with control and noise acting on a subdomain.     

Stochastic viscosity solutions for SPDEs with continuous coefficients

In this note, nonlinear stochastic partial differential equations (SPDEs) with continuous coefficients are studied. Via the solutions of backward doubly stochastic differential equations (BDSDEs) with continuous coefficients, we provide an existence result of stochastic viscosity sub- and super-solutions to this class of SPDEs. Under some stronger conditions, we prove the existence of stochastic viscosity solutions.