非Lipschitz条件下混合型随机微分方程解的矩估计北大核心CSCD

本文的研究对象为非Lipschitz条件下混合分数布朗运动驱动的随机微分方程.混合分数布朗运动是布朗运动和分数布朗运动的线性组合.通过证明和混合分数布朗运动有关的伊藤公式,借助Malliavin积分理论,本文证明在非Lipschitz条件下,由混合分数布朗运动驱动的随机微分方程解的矩估计和连续性.     

一类多维参数高斯过程的弱逼近

本文研究了一类多维参数高斯过程的弱极限问题.在一般情况下,利用泊松过程得到了此类过程的弱极限定理,此多维参数高斯过程可表示为确定的核函数关于维纳过程的随机积分,且包含多维参数的分数布朗运动.     

布朗运动对某些集的首中时分布

首中时是近代马氏过程中的一个重要概念.作为强马氏过程的布朗运动,其首中时在位势理论的 Dirichlet 问题与平衡问题中,都是一个关键性的量.首中时分布函数在上述问题中都处于重要地位。特别,已经证明〔1〕,它是热传导方程在一定初始条件与边值条件下的唯一解。因此,求布朗运动对各种集的首中时分布函数,就成了近代布朗运     

Besov空间上Riemann-Liouville型重分数布朗单的弱收敛[英文]

本文研究Besov空间上Riemann-Liouville型重分数布朗单的弱收敛问题.分别利用平面上的Poisson过程和两列独立的Riemann-Liouville型重分数布朗运动的部分和,构造了Riemann-Liouville型重分数布朗单的弱极限定理.     

关于分数布朗运动预测的研究

本文对赫斯特参数H∈(1/2,1)的分数布朗运动的预测过程的样本轨道性质进行了讨论.利用布朗运动的随机积分理论,建立了一个重要的不等式,证明了(Z)的图集的Hausdorff维数等于1,得出了预测过程与分数布朗运动本身有显著不同特征的结论.     

局部Lipschitz条件下的布朗运动和泊松过程混合驱动的正倒向随机微分方程

本文得到在局部Lipschiz条件下的布朗运动和泊松过程混合驱动的倒向随机微分方程的存在唯一性；同时也证明了布朗运动和泊松过程混合驱动的完全藕合的正倒向随机微分方程在局部Lipschitz条件下的解的存在唯一性。     

布朗随机流动形:白噪声分析方法

本文在经典白噪声分析框架下,用一种新的方法研究随机流动形. 首先使用布朗运动的Wick积分定义Wick型随机流动形.进一步, 用白噪声分析方法和S-变换证明：布朗随机流动形可视为Hida广义泛函.     

利用Ito公式求布朗运动和几何布朗运动的矩

利用Ito公式及Ito积分的性质求出了布朗运动和几何布朗运动的矩的一般形式,同时指出可以利用这种方法求其他扩散过程的矩.     

标准布朗运动关于曲线边界通过概率

布朗运动是一种重要的随机过程,它的首出时的分布在很多方面有着重要的应用.该文讨论了布朗运动关于任意曲线边界的首出时的问题,求出了布朗运动停在双侧(单侧)曲线边界内的概率的分析表达式.     

混合分数布朗运动环境下欧式期权定价

假设股票价格变化过程服从混合分数布朗运动,建立了混合分数布朗环境下支付连续红利的欧式股票期权的定价模型.利用混合分数布朗运动的It-公式,将支付连续红利的欧式股票期权的定价问题转化为一个偏微分方程,通过偏微分方程求解获得了混合分数布朗运动环境下支付连续红利的欧式股票看涨期权的定价公式.     

SPDE with generalized drift and fractional-type noise

We consider a stochastic partial differential equation involving a second order differential operator whose drift is discontinuous. The equation is driven by a Gaussian noise which behaves as a Wiener process in space and the time covariance generates a signed measure. This class includes the Brownian motion, fractional Brownian motion and other related processes. We give a necessary and sufficient condition for the existence of the solution and we study the path regularity of this solution.     

On time‐dependent stochastic evolution equations driven by fractional Brownian motion in a Hilbert space with finite delay

In this paper, we show the existence and uniqueness of the mild solution for a class of time‐dependent stochastic evolution equations with finite delay driven by a standard cylindrical Wiener process and an independent cylindrical fractional Brownian motion with Hurst parameter H ∈ (1 / 2,1). An example is provided to illustrate the theory. Copyright © 2013 John Wiley & Sons, Ltd.     

Symmetric stochastic integrals with respect to p-adic Brownian motion†

In this paper, we consider complex-valued Brownian motion with p-adic time index and the associated abstract Wiener space. We define symmetric stochastic integrals with respect to p-adic Brownian motion. We also provide a sufficient condition for the existence of symmetric stochastic integrals and present a relation to the adjoint of the Malliavin derivatives.     

Banach Space-Valued Ornstein–Uhlenbeck Processes with General Drift Coefficients

We construct Ornstein–Uhlenbeck processes with values in Banach space and with continuous paths. The drift coefficient must only generate a strongly continuous semigroup on the Hilbert space which determines the Brownian motion. We admit arbitrary starting points and consider also invariant measures for the process, generalizing earlier work in many directions. A price for the generality is that sometimes one has to enlarge the phase space but most previously known results are covered.The constructions are based on abstract Wiener space methods, more precisely on images of abstract Wiener spaces under suitable linear transformations of the Cameron–Martin space. The image abstract Wiener measures are then given by stochastic extensions. We present the basic spaces and operators and the most important results on image spaces and stochastic extensions in some detail.     

Large Deviations from the Almost Everywhere Central Limit Theorem

We prove large deviation principles for the almost everywhere central limit theorem, assuming that the i.i.d. summands have finite moments of all orders. The level 3 rate function is a specific entropy relative to Wiener measure and the level 2 rate the Donsker-Varadhan entropy of the Ornstein-Uhlenbeck process. In particular, the rate functions are independent of the particular distribution of the i.i.d. process under study. We deduce these results from a large deviation theory for Brownian motion via Skorokhod's representation of random walk as Brownian motion evaluated at random times. The results for Brownian motion come from the well-known large deviation theory of the Ornstein-Uhlenbeck process, by a mapping between the two processes.     

Existence for dynamic contact of a stochastic viscoelastic Gao Beam

This work presents and analyzes a model for the vibrations of a viscoelastic Gao Beam, which may come in contact with a deformable random foundation and allows for stochastic inputs. The body force involves a stochastic integral that includes Brownian motion. In addition, the gap between the beam and the foundation is a stochastic process, which is one of the novelties in the paper, and contact is described with the normal compliance condition. The existence and uniqueness of strong solutions to the model is established and it is shown that the solutions are adapted to the filtration determined by a given Wiener process for the stochastic force noise term.     

Pinning class of the Wiener measure by a functional: related martingales and invariance properties

For a given functional Y on the path space, we define the pinning class of the Wiener measure as the class of probabilities which admit the same conditioning given Y as the Wiener measure. Using stochastic analysis and the theory of initial enlargement of filtration, we study the transformations (not necessarily adapted) which preserve this class. We prove, in this non Markov setting, a stochastic Newton equation and a stochastic Noether theorem. We conclude the paper with some non canonical representations of Brownian motion, closely related to our study.Mathematics Subject Classification (2000): 60G44, 60H07, 60H20, 60H30     

混合型随机微分方程的传输不等式

该文探讨一类由Wiener过程和Hurst参数1/2＜H＜1分数布朗运动驱动的混合型随机微分方程.通过使用一些变换技巧和逼近方法,这类方程的强解在d2度量和一致度量d∞下的二次传输不等式被建立.     

Wiener integrals, Malliavin calculus and covariance measure structure

We introduce the notion of covariance measure structure for square integrable stochastic processes. We define Wiener integral, we develop a suitable formalism for stochastic calculus of variations and we make Gaussian assumptions only when necessary. Our main examples are finite quadratic variation processes with stationary increments and the bifractional Brownian motion.     

General Autoregressive Models with Long-Memory Noise

We give the limiting distribution of the least-squares estimator in the general autoregressive model driven by a long-memory process. We prove that with an appropriate normalization the estimation error converges, in distribution, to a random vector which contains: (1) a stochastic component, due to the presence of the unstable roots, which are multiple Wiener–Itô integrals and a non-linear functionals of stochastic integrals with respect to a Brownian motion; (2) a constant component due to the stable roots; (3) a stochastic component, due to the presence of the explosive roots, which is a mixture of normal distributions.