迭代过程及其在高阶微分方程中的应用

通过对布朗运动和电报过程的适当迭代,使之迭代过程的转移函数满足不同形式的高阶抛物型或双曲型微分方程．对迭代过程进行适当的时间变换,还可以使迭代过程的转移函数满足系数依赖于时间的高阶微分方程．本文还讨论了迭代布朗运动最大值的分布及其有关性质．     

高阶偏微分方程与概率方法

二阶偏微分方程与扩散过程的是概率界众所财知的。前者为后者提供了分析依据，后者为前者的解给出了概率表示；如何把这种联系推广到高阶偏微分方程的情形，是很多概率学家近十几年来一直关心的问题。     

随机偏微分方程——建模,分析与有效动力学

综述随机偏微分方程的基本概念、理论、方法与应用,内容包括Hilbert空间中的Wiener过程、Ito随机积分、随机偏微分方程的解及其有效动力学。还介绍了随机偏微分方程的粗糙轨道、正则结构以及在Kardar-ParisiZhang(KPZ)方程中的应用。还介绍了段金桥与王伟的著作《Effective Dynamics of Stochastic Partial Differential Equations(随机偏微分方程的有效动力学)》的基本内容。     

Backward Doubly Stochastic Differential Equations with Jumps and Stochastic Partial Differential-Integral Equations

Backward doubly stochastic differential equations driven by Brownian motions and Poisson process(BDSDEP) with non-Lipschitz coeffcients on random time interval are studied.The probabilistic interpretation for the solutions to a class of quasilinear stochastic partial differential-integral equations(SPDIEs) is treated with BDSDEP.Under non-Lipschitz conditions,the existence and uniqueness results for measurable solutions to BDSDEP are established via the smoothing technique.Then,the continuous dependence for solutions to BDSDEP is derived.Finally,the probabilistic interpretation for the solutions to a class of quasilinear SPDIEs is given.     

The Link between Stochastic Differential Equations with Non-Markovian Coefficients and Backward Stochastic Partial Differential Equations

In this paper, we conjecture and prove the link between stochastic differential equations with non-Markovian coefficients and nonlinear parabolic backward stochastic partial differential equations, which is an extension of such kind of link in Markovian framework to non-Markovian framework.Different from Markovian framework, where the corresponding partial differential equation is deterministic, the backward stochastic partial differential equation here has a pair of adapted solutions, and thus the link has a much different form. Moreover, two examples are given to demonstrate the applications of the derived link.     

Iterated Logarithm Law for Anticipating Stochastic Differential Equations

We prove a functional law of iterated logarithm for the following kind of anticipating stochastic differential equations

Stochastic Control for Mean-Field Stochastic Partial Differential Equations with Jumps

We study optimal control for mean-field stochastic partial differential equations (stochastic evolution equations) driven by a Brownian motion and an independent Poisson random measure, in case of partial information control. One important novelty of our problem is represented by the introduction of general mean-field operators, acting on both the controlled state process and the control process. We first formulate a sufficient and a necessary maximum principle for this type of control. We then prove the existence and uniqueness of the solution of such general forward and backward mean-field stochastic partial differential equations. We apply our results to find the explicit optimal control for an optimal harvesting problem.     

High Order Semi-implicit Multistep Methods for Time-Dependent Partial Differential Equations

We consider the construction of semi-implicit linear multistep methods that can be applied to time-dependent PDEs where the separation of scales in additive for...     

Derivation of Stochastic Partial Differential Equations

Abstract

A procedure is explained for deriving stochastic partial differential equations from basic principles. A discrete stochastic model is first constructed. Then, a stochastic differential equation system is derived, which leads to a certain stochastic partial differential equation. To illustrate the procedure, a representative problem is first studied in detail. Exact solutions, available for the representative problem, show that the resulting stochastic partial differential equation is accurate. Next, stochastic partial differential equations are derived for a one-dimensional vibrating string, for energy-dependent neutron transport, and for cotton-fiber breakage. Several computational comparisons are made.     

Tsirel'son's Example for Stochastic Partial Differential Equations

We give an example of a stochastic partial diferential equation which has no strong solution even though it has a solution on an appropriate stochastic basis.     

Averaging of Backward Stochastic Differential Equations and Homogenization of Partial Differential Equations with Periodic Coefficients

Abstract

We study the limit of the solutions of systems of semi-linear partial differential equations (PDEs) of second order of parabolic type, with rapidly oscillating periodic coefficients, a singular drift, and singular coefficients of the zero and second order terms. Our basic tool is the approach given by Pardoux [14 Pardoux , E. 1999 . Homogenization of linear and semilinear second order parabolic PDEs with periodic coefficients: a probabilistic approach . J. Funct. Anal. 167 : 498 – 520 . [CSA] [CROSSREF] [Crossref], [Web of Science ®] , [Google Scholar]]. In particular, we use the weak convergence of an associated backward stochastic differential equation (BSDE).     

Composition of Processes and Related Partial Differential Equations

In this paper various types of compositions involving independent fractional Brownian motions B^j_Hj(t)B^{j}_{H_{j}}(t), t>0, j=1,2, are examined.     

一类具连续分布滞量的高阶偏微分方程的振动性

研究一类具有连续分布滞量中立项的非线性偏微分方程解的振动性,得到该方程在给定边值条件下振动和非振动的一些充分条件.     

The Numerical Approximation of Stochastic Partial Differential Equations

The numerical solution of stochastic partial differential equations (SPDEs) is at a stage of development roughly similar to that of stochastic ordinary differential equations (SODEs) in the 1970s, when stochastic Taylor schemes based on an iterated application of the Itô formula were introduced and used to derive higher order numerical schemes. An Itô formula in the generality needed for Taylor expansions of the solution of a SPDE is however not available. Nevertheless, it was shown recently how stochastic Taylor expansions for the solution of a SPDE can be derived from the mild form representation of the SPDE, which avoid the need of an Itô formula. A brief review of the literature is given here and the new stochastic Taylor expansions are discussed along with numerical schemes that are based on them. Both strong and pathwise convergence are considered.     

从超布朗运动到随机偏微分方程

随机偏微分方程(SPDE)是目前国内外广泛关注研究进展迅速的一个活跃的学术研究领域.该主题的研究涉及概率论(随机分析、随机场)、偏微分方程、调和分析等诸多分支学科方向.特别是随机偏微分方程其背景更多地源于现代物理学、化学、生物学、经济学等应用性学科,这使得该领域的研究显示出较强的意义和活力.本文从超布朗运动研究出发,发展性地提出有较强背景意义的典型类随机偏微分方程,并进而过渡到一般及更广泛类的随机偏微分方程的研究.同时我们系统地总结了关于高阶随机偏微分方程和随机波动方程的研究成果.     

High Speed Flight and Partial Differential Equations*

Chinese Annals of Mathematics, Series B - Aircraft comes out at the beginning of the last century. Accompanied by the progress of high speed flight the theory of partial differential equations has...     

关于高阶中立型偏微分方程系统解的振动性

近年来,由于偏泛函微分方程(组)理论在人口动力学,生物遗传工程和化学反应过程等领域中有广泛的应用,因而很多学者在偏泛函微分方程(组)解的振动性理论的研究方面做了大量工作,取得了许多成果.本文将研究一类较广泛的高阶中立型偏微分方程组