倒向随机Volterra积分方程适应解的表示

倒向随机Volterra积分方程可以看作(确定性)Volterra积分方程和倒向随机微分方程的推广,在随机最优控制理论和数学金融学中有诸多应用.本文利用正倒向随机微分方程适应解表示的思想,得到所研究的一类倒向随机Volterra积分方程适应解的表示.这样的结果对研究适应解的正则性以及数值计算有重要的意义.     

带有弱奇性核的多项分数阶非线性随机微分方程解的适定性

本文主要研究一类带有多项分数阶Caputo导数的非线性随机微分方程初值问题的解的适定性.具体地,首先把多项分数阶随机微分方程等价地转化为随机Volterra积分方程;然后,给出了该随机积分方程的Euler-Maruyama (EM)格式;最后,借助于该EM格式,证明了多项分数阶随机微分方程的解的适定性.     

由分数布朗运动驱动的随机微分方程的比较定理及其应用

本文研究了由分数布朗运动驱动的不同扩散和漂移系数随机微分方程.利用随机微分方程广义样本解的方法,得到了两个比较定理.进一步,给出了他们的应用和一个最优逼近策略.     

半圆域内的二维线性椭圆偏微分方程

本文研究了半圆域内的二维线性椭圆偏微分方程.利用Fokas提出的求解凸多边形区域内的线性椭圆偏微分方程的变换方法,我们改进了这个方法来研究半圆域内Laplace方程,修改Helmholtz方程和Helmholtz方程的解,并且导出了这些方程解的积分表达式,讨论了Helmholtz方程的广义Dirichlet到Neumann映射.     

由分数布朗运动驱动的随机微分方程的比较定理及其应用（英文）

本文研究了由分数布朗运动驱动的不同扩散和漂移系数随机微分方程.利用随机微分方程广义样本解的方法,得到了两个比较定理.进一步,给出了他们的应用和一个最优逼近策略.     

半圆域内的二维线性椭圆偏微分方程（英文）

本文研究了半圆域内的二维线性椭圆偏微分方程.利用Fokas提出的求解凸多边形区域内的线性椭圆偏微分方程的变换方法,我们改进了这个方法来研究半圆域内Laplace方程,修改Helmholtz方程和Helmholtz方程的解,并且导出了这些方程解的积分表达式,讨论了Helmholtz方程的广义Dirichlet到Neumann映射.     

(3+1)-维广义随机KP方程的精确解

利用统一方式构造非线性偏微分方程行波解的广义Jacobi椭圆函数展开法和Hermite变换来研究(3+1)-维广义随机KP方程,给出了它的随机对偶周期和多孤子解.     

分数Brown运运动驱动的非Lipschitz随随机微分方程

讨论了一类带分数Brown运动的非Lipschitz增长的随机微分方程适应解的存在唯一性.关于分数Brown运动的随机积分有多种定义,本文使用一种广义Stieltjes积分定义方法,利用这种积分的性质,建立了一类由标准Brown运动和一个Hurst指数H∈(1/2,1)的分数Brown运动共同驱动的、系数为非Lipschitz增长的随机微分方程适应解的存在唯一性定理.     

带分数Brown运动和局部线性增长的随机微分方程

该文讨论了一类带分数Brown运动,且系数为局部线性增长的随机微分方程适应解的存在唯一性.使用一种广义tieltjes积分定义方法定义关于分数Brown运动的随机积分,利用这种积分的性质,得到了一类由标准Brown运动和一个Hurst指数H∈(1/2,1)的分数Brown运动共同驱动的、系数为局部线性增长的随机微分方程适应解的存在唯一性结果.     

两类破碎群体平衡方程接受的李群及群不变解

针对难找到破碎群体平衡方程的精确解和解析方法缺乏的问题,研究两类积分-偏微分方程(破碎群体平衡方程)接受的李群、群不变解、约化积分-常微分方程及精确解.首先采用伸缩变换李群分析方法探寻积分-偏微分方程接受的李群.其次将积分-偏微分方程转化为纯偏微分方程,运用经典李群分析方法计算纯偏微分方程接受的李群.然后利用改进了的李群分析方法结合伸缩变换群和经典李群分析方法获得的结果确定积分-偏微分方程接受的李群.最后找到了积分-偏微分方程接受的李群,给出了积分-偏微分方程的约化积分-常微分方程、群不变解及显式精确解,分析了部分解的动力学行为性质及特征.     

On the Convergence of Coderivative of SAA Solution Mapping for a Parametric Stochastic Generalized Equation

The aim of this paper is to investigate the convergence properties for Mordukhovich’s coderivative of the solution map of the sample average approximation (SAA) problem for a parametric stochastic generalized equation. It is demonstrated that, under suitable conditions, both the cosmic deviation and the ρ-deviation between the coderivative of the solution mapping to SAA problem and that of the solution mapping to the parametric stochastic generalized equation converge almost surely to zero as the sample size tends to infinity. Moreover, the exponential convergence rate of coderivatives of the solution maps to the SAA parametric generalized equations is established. The results are used to develop sufficient conditions for the consistency of the Lipschitz-like property of the solution map of SAA problem and the consistency of stationary points of the SAA estimator for a stochastic mathematical program with complementarity constraints.     

A New Generalized Gronwall Inequality with a Double Singularity and Its Applications to Fractional Stochastic Differential Equations

Abstract

In many cases, the existence and uniqueness of the solution of a differential equation are proved using fixed point theory. In this paper, we utilize the theory of operators and ingenious techniques to investigate the well-posedness of mild solution to semilinear fractional stochastic differential equations. We first discuss some properties of a class of Volterra integral operators and then establish a new generalized Gronwall integral inequality with a double singularity. Finally, we use the properties and integral inequality to study the well-posedness of mild solution to the semilinear fractional stochastic differential equations. One sees that it is concise and effectiveness using the previous results to investigate the well-posedness of the mild solution.     

Nonlinear flows of stochastic linear delay equations

The sample non-linearity of the classical Wiener integral as a function of continuous integrands is pointed out. As an application it is shown that the solution of a linear stochastic delay equation is an almost surely non-linear function of the initial trajectory segment.     

A “direct” method to prove the generalized Itô–Venttsel’ formula for a generalized stochastic differential equation

For the first time we present a complete proof (from the standpoint of stochastic analysis) of the generalized Itô–Venttsel’ formula whose ideas were adduced in [8]. The proposed proof is an approach to construct the generalized Itô–Venttsel’ formula based on the direct application of the generalized Itô formula and the theory of stochastic approximation in contrast to the proof presented in [17] and based on the method of the integral invariants of a stochastic differential equation.     

Integral representation of generalized grey Brownian motion

ABSTRACT

In this paper, we investigate the representation of a class of non-Gaussian processes, namely generalized grey Brownian motion, in terms of a weighted integral of a stochastic process which is a solution of a certain stochastic differential equation. In particular, the underlying process can be seen as a non-Gaussian extension of the Ornstein–Uhlenbeck process, hence generalizing the representation results of Muravlev, Russian Math. Surveys 66 (2), 2011 as well as Harms and Stefanovits, Stochastic Process. Appl. 129, 2019 to the non-Gaussian case.     

An Integral-Equqtion Approach for Replacement Modelling Over Finite Time Horizons

An integral-equation approach to calculating the exact and asymptoticestimates of expected costs in stochastic replacemnet problemsis advocated. The method is based upon the known solution tothe generalized renewal integral equation and upon the key renewaltheorem. The basic failure-bsed and age-based replacement policiesare taken as illustrative examples for the method, and the relationshipto more conventional methods of calculation is highlighted.The benefit of the integral-equation format is that it providesa relatively clear procedure for evaluating more complex stochastitreplacement situations.     

Numerical Solution Based on Hat Functions for Solving Nonlinear Stochastic Itô Volterra Integral Equations Driven by Fractional Brownian Motion

This paper presents a numerical method for solving nonlinear stochastic Itô Volterra integral equations driven by fractional Brownian motion with Hurst parameter \( H \in (0,1)\) via of hat functions. Using properties of the generalized hat basis functions and fractional Brownian motion, new stochastic operational matrix of integration is achieved and the nonlinear stochastic equation is transformed into nonlinear system of algebraic equations which by solving it, an approximation solution with high accuracy is obtained. In addition, error analysis of the method is investigated, and by some examples, efficiency and accuracy of the suggested method are shown.     

Generalized Reflected BSDE and an Obstacle Problem for PDEs with a Nonlinear Neumann Boundary Condition

Abstract

In this article, we derive the existence and uniqueness of the solution for a class of generalized reflected backward stochastic differential equation involving the integral with respect to a continuous process, which is the local time of the diffusion on the boundary, in using the penalization method. We also give a characterization of the solution as the value function of an optimal stopping time problem. Then we give a probabilistic formula for the viscosity solution of an obstacle problem for PDEs with a nonlinear Neumann boundary condition.     

Stochastic equations for two-type continuous-state branching processes with immigration and competition

A class of two-type continuous-state branching processes with immigration and competition is constructed as the solution of a jump-type stochastic integral equation system. We first show that the stochastic equation system has a pathwise unique non-negative strong solution and then prove the comparison property of the solution.     

Stochastic equations for two-type continuous-state branching processes with immigration

A two-dimensional stochastic integral equation system with jumps is studied. We first prove its unique weak solution is a two-type continuous-state branching process with immigration. Then the comparison property of the solution is established. These results imply the existence and uniqueness of the strong solution of the stochastic equation system.