随机狄里克莱级数的收敛性

该文是利用随机变量序列的局部收敛性及强大数定律研究了随机狄里克莱级数的收敛性,得出了它的收敛横坐标的简洁公式．     

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.     

随机加权U-过程的条件弱收敛

假定Ｆ是一个由函数组成的集合．在这篇文章中,我们研究了指标集Ｆ上２阶的随机加权Ｕ－过程的条件弱收敛性质,导出了Ｕ－过程的随机加权逼近．     

Generating a Random Signed Permutation with Random Reversals

Signed permutations form a group known as the hyperoctahedral group. We bound the rate of convergence to uniformity for a certain random walk on the hyperoctahedral group that is generated by random reversals. Specifically, we determine that O(n log n) steps are both necessary and sufficient for total variation distance and ℓ² distance to become small. This random walk arose as the result of an effort in molecular biology to model certain types of genome rearrangements.     

随机模糊集与随机集

本文研究了三个方面的工作：一是定义了一种模糊集上的可测结构，从而定义了随机模糊集，这些定义都与论域Ｘ上的拓扑结构无关。将通常意义下的集合看成特殊模糊集得到的通常集合上的超可测结构与文（３）中的定义一致；二是给出了随机模糊集、随机集的一些等价条件；三是研究了随机模糊集、随机集的分布与其有限维落影族的关系。     

The Law of Large Numbers and the Ito-Nisio Theorem for Vector Valued Random Fields

Strong convergence results are obtained for vector-valued random fields. Substantial development of Banach-valued random fields and summability results is needed to provide the framework for the major results since many plausible extensions fail for multi-indexed Banach-valued random variables. This development yields general convergence results for random fields in Banach spaces, including an Ito-Nisio theorem and strong laws of large numbers.     

随机环境中迁入分枝过程的极限性质

在方差和均值有限的条件下,得到了随机环境中迁入分枝过程对应的规范化过程的几乎处处收敛性和L^2收敛性．这对于刻画过程本身的发散速度,具有重要的意义．     

Random Completely Generalized Set-Valued Implicit Quasi-Variational Inequalities

The purpose of this paper is to introduce a class of new random completely generalized set-valued implicit quasi-variational inequalities, to construct new random iterative algorithms, and to give some existence theorems of random solutions for this class of random completely generalized set-valued implicit quasi-variational inequalities. We also prove the convergence of random iterative sequences generated by the algorithms. Our results extend and improve the earlier and recent results.     

关于投影算子随机乘积序列的收敛性

投影算子随机乘积的收敛性奠定广泛应用数学方法的理论基础,本文将在某些宽松条件下研究并肯定回答有关投影算子随机乘积序列收敛性的两个问题．     

随机环境中有界跳幅随机游动常返性暂留性的另一证明

假定环境是平稳遍历的,对具有有限跳幅的随机环境中的随机游动,该文给出了其常返性暂留性的另一证明.Bremont(2002)的文章中,通过计算逃逸概率的方法给出了证明,而该文的证明采用了鞅收敛定理的方法.     

Random iterations of holomorphic maps in complex Banach spaces

Conditions guaranteeing the uniform convergence to constant maps of random iterations of holomorphic contractions on unbounded domains in complex Banach spaces are established.

     

Uniform Convergence of Wavelet Expansions of Gaussian Random Processes

New results on uniform convergence in probability for the most general classes of wavelet expansions of stationary Gaussian random processes are given.     

Random walks in cones: The case of nonzero drift

We consider multidimensional discrete valued random walks with nonzero drift killed when leaving general cones of the euclidean space. We find the asymptotics for the exit time from the cone and study weak convergence of the process conditioned on not leaving the cone. We get quasistationarity of its limiting distribution. Finally we construct a version of the random walk conditioned to never leave the cone.     

任意随机序列关于二重非齐次马氏链的随机和的一类随机选择系统的随机逼近定理

本文引进任意随机变量序列随机极限对数似然比的概念,通过测度$\pr$下任意相依随机序列联合分布与测度$\qr$下二重非齐次马氏分布相比较,利用母函数与尾概率母函数工具研究任意受控随机序列之随机和在随机选择系统中的一类随机逼近定理.     

Strong Law of Large Numbers for Stationary Sequences of Random Upper Semicontinuous Functions

Abstract

The strong laws of large numbers with the convergence in the sense of the uniform Hausdorff metric for stationary sequences of random upper semicontinuous functions is established. This approach allows us to deduce many results on the convergence in uniform Hausdorff metric of random upper semicontinuous functions from the relevant results on real-valued random variables that appear as their support functions.     

Approximation for the Normal Inverse Gaussian Process Using Random Sums

Abstract

We approximate the normal inverse Gaussian (NIG) process with random summations. The random sum we introduce is a random walk subordinated to the first passage time of another independent random walk; the model is interpreted as an internal mechanism at small scale that generates the NIG process. The main result is a functional limit theorem of weak convergence in the Skorohod topology.     

B值随机元阵列的完全收敛性及大数定律

该文在随机元阵列随机有界于某非负随机变量的条件下，得到了B值随机元阵列完全收敛性的一般性结论，并讨论了随机元阵列加权和的收敛性，使[5][6]中的结果得到了改进和推广．同时讨论了完全收敛性与Banach空间p型（1＜P≤2）性质的等价性，使[14]，[15]中的结果得到进一步的改进．     

一类随机算子方程随机解的存在性

研究了一类随机算子方程的随机解，推广了几个重要的定理. 同时，得到了若干新的结果.      

Stochastic Integration Based on Simple, Symmetric Random Walks

A new approach to stochastic integration is described, which is based on an a.s. pathwise approximation of the integrator by simple, symmetric random walks. Hopefully, this method is didactically more advantageous, more transparent, and technically less demanding than other existing ones. In a large part of the theory one has a.s. uniform convergence on compacts. In particular, the method gives a.s. convergence for the stochastic integral of a finite variation function of the integrator, which is not càdlàg in general. Research of T. Szabados was supported by a Hungarian National Research Foundation (OTKA) grant No. T42496. Research of B. Székely was supported by the HSN laboratory of BUTE.     

Robustness of Random Attractors for a Stochastic Reaction-Diffusion System

Asymptotic pullback dynamics of a typical stochastic reaction-diffusion system, the reversible Schnackenberg equations, with multiplicative white noise is investigated. The robustness of random attractor with respect to the reverse reaction rate as it tends to zero is proved through the uniform pullback absorbing property and the uniform convergence of reversible to non-reversible cocycles. This result means that, even if the reverse reactions would be neglected, the dynamics of this class of stochastic reversible reaction-diffusion systems can still be captured by the random attractor of the non-reversible stochastic raction-diffusion system in a long run.