随机耗散Camassa-Holm方程的吸引子

可以接轨道得到带白噪声的随机耗散Camassa-Holm方程的唯—解并且可以检验该解产生随机动力系统,从而证明了该随机动力系统在H₀²中存在紧的随机吸引子.     

带加法白噪声的随机三维Camassa-Holm模型的H~2-吸引子

研究带加法白噪声的三维Camassa-Holm模型的随机动力性.通过验证解满足随机Flattening条件,得到随机动力系统的w-极限紧性.然后,利用李和郭关于拟连续随机动力系统的结果,获得该模型的随机动力性的H~2-吸引子描述.     

一类非自治分数阶随机波动方程的随机吸引子

本文考虑带加性噪声的非自治分数阶随机波动方程在无界区域R~n上的渐近行为.首先将随机偏微分方程转化为随机方程,其解产生一个随机动力系统,然后运用分解技术建立该系统的渐近紧性,最后证明随机吸引子的存在性.     

带附加噪声的随机广义2D Ginzburg-Landau方程的渐进行为

考虑带附加噪声的随机广义2D Ginzburg-Landau方程.通过先验估计的方法,随机动力系统的紧性得到证明,进一步验证了该随机动力系统在础存在随机整体吸引子.     

弱拓扑下的非线性随机积分和微分方程组的解*

在本文中,我们首先对具有随机定义域的弱连续随机算子组证明了一个Darbo型随机不动点定理.利用这一定理,我们对Banach空间中关于弱拓扑的非线性随机Volterra积分方程组给出了随机解的存在性准则.作为应用,我们得到了非线性随机微分方程组的Canchy问题弱随机解的存在定理.也得到了这些随机方程组在Banach空间中关于弱拓扑的极值随机解的存在性和随机比较结果.我们的定理改进和推广了Szep,Mitchell－Smith,Cramer－Lakshmikantham,Lakshmikantham-Leela和丁的相应结果.     

随机广义Ginzburg-Landau方程的吸引子

可以按轨道得到带白噪声的随机广义Ginzburg-Landau方程的唯一解并且能够验证该解可以产生随机系统, 从而证明了该随机系统在H¹₀中存在整体随机吸引子.     

非线性随机积分和微分方程组的解*

在本文中我们首先对具有随机定义域的连续随机算子组证明了Darbao型不动点定理。应用此定理我们给出了非线性随机Volterra积分方程组和非线性随机微分方程组的Cauchy问题解的存在性准则。这些随机方程组的极值随机解的存在性和随机比较结果也被获得。我们的定理改进和推广Tyaughn,Lakshmikantham,Lakshmikantham-Leela,DeBlast-Myjak和第一作者的相应结果。     

随机反应扩散方程的L~P-随机吸引子

研究了定义在无界区域上具可乘白噪音的随机反应扩散方程的渐近行为.运用一致估计得到了U3-随机吸收集;对方程的解运用渐近优先估计法,建立了相应随机动力系统的渐近紧性,证明了LP-随机吸引子的存在性.该随机吸引子是紧不变集并按LP-范数吸L2中所有缓增集,其中,非线性项/满足p-1(p≥2)阶增长条件.     

具有乘积噪声的非自治Swift-Hohenberg方程在无界区域上的渐近性（英文）

本文研究R~2上带有时间依赖外力项与乘性噪声的随机非自治修正Swift-Hohenberg方程的动力行为.为了克服无界域上Sobolev嵌入不紧的困难,我们先定义了问题在L~2(R~2)上的连续共圈,并且建立了当空间变量足够大时,解尾部的一致估计.通过解的一致估计,我们证明了随机动力系统的拉回渐近紧性,进一步得到了随机吸引子的存在性.     

随机系数线性方程组正解的一种数值解法

通过建立摩擦片磨损量的数学模型,引出了随机系数线性方程组的求解问题以及对其解的统计分布上的分析,给出了一个相关定理,阐明了其分布是对称分布,且其正分量出现的概率大于零,从而为讨论此类方程组解的问题提供了统计分析的依据.同时,还利用优化思想对该随机系数线性方程组的正解加以讨论,给出在简约梯度法下正解数值近似解的算例.     

Random attractor for stochastic second-order non-autonomous stochastic lattice equations with dispersive term

In this paper, we consider the asymptotic behaviour of solutions to second-order non-autonomous stochastic lattice equations with dispersive term and additive white noises in the space of infinite sequences. We first transfer the stochastic lattice equations into random lattice equations, and prove the existence and uniqueness of solutions that generate a random dynamical system. Second, we prove the existence of a tempered random absorbing set and a random attractor for the system. Finally, we establish the upper semi-continuity of the random attractors as the coefficient of the white noise term tends to zero.     

Asymptotic autonomous attractors for a stochastic lattice model with random viscosity

We study forward asymptotic autonomy of a pullback random attractor for a non-autonomous random lattice system and establish the criteria in terms of convergence, recurrence, forward-pullback absorption and asymptotic smallness of the discrete random dynamical system. By applying the abstract result to both non-autonomous and autonomous stochastic lattice equations with random viscosity, we show the existence of both pullback and global random attractors such that the time-component of the pullback attractor semi-converges to the global attractor as the time-parameter tends to infinity.     

Random attractors of stochastic partial differential equations: A smooth approximation approach

We use the method of smooth approximation to examine the random attractor for two classes of stochastic partial differential equations (SPDEs). Roughly speaking, we perturb the SPDEs by a Wong-Zakai scheme using smooth colored noise approximation rather than the usual polygonal approximation. After establishing the existence of the random attractor of the perturbed system, we prove that when the colored noise tends to the white noise, the random attractor of the perturbed system with colored noise converges to that of the original SPDEs by invoking some continuity results on attractors in random dynamical systems.     

Large deviations for the Boussinesq equations under random influences

A Boussinesq model for the Bénard convection under random influences is considered as a system of stochastic partial differential equations. This is a coupled system of stochastic Navier–Stokes equations and the transport equation for temperature. Large deviations are proved, using a weak convergence approach based on a variational representation of functionals of infinite-dimensional Brownian motion.     

Rare events in the Boussinesq system with fluctuating dynamical boundary conditions

The Boussinesq system models various phenomena in geophysical and climate dynamics. It is a coupled system of the Navier-Stokes equations and the salinity transport equation. Due to uncertainty in salinity flux on fluid boundary, this system is subject to random fluctuations on the boundary. This stochastic Boussinesq system can be transformed into a random dynamical system. Rare events, or small probability events, are investigated in the context of large deviations. A large deviations principle is established via a weak convergence approach based on a recently developed variational representation of functionals of infinite dimensional Brownian motion.     

Random attractors for stochastic differential equations driven by two-sided Lévy processes

Abstract

In this paper, the asymptotic behavior of solutions for a nonlinear Marcus stochastic differential equation with multiplicative two-sided Lévy noise is studied. We plan to consider this equation as a random dynamical system. Thus, we have to interpret a Lévy noise as a two-sided metric dynamical system. For that, we have to introduce some fundamental properties of such a noise. So far most studies have only discussed two-sided Lévy processes which are defined by combining two-independent Lévy processes. In this paper, we use another definition of two-sided Lévy process by expanding the probability space. Having this metric dynamical system we will show that the Marcus stochastic differential equation with a particular drift coefficient and multiplicative noise generates a random dynamical system which has a random attractor.     

Sample-Path Stability of Non-Stationary Dynamic Economic Systems

The goal of this paper is to introduce and illustrate a new approach to the stability analysis of sample-paths of non-linear stochastic economic models with non-stationary components. We place our study within the mathematical theory of random dynamical systems and apply the concept of a random fixed point which is tailor-made for the study of the long-term behavior of sample-paths in stochastic systems. The main tool for the application of this approach is a Banach-type fixed point theorem for non-stationary random dynamical systems which is proved here. The concept and the theorem are thoroughly explained and illustrated by examples from stochastic growth theory.     

Invariant manifolds for stochastic wave equations

In this paper, we consider a class of stochastic wave equations with nonlinear multiplicative noise. We first show that these stochastic wave equations generate random dynamical systems (or stochastic flows) by transforming the stochastic wave equations to random wave equations through a stationary random homeomorphism. Then, we establish the existence of random invariant manifolds for the random wave equations. Due to the temperedness of the nonlinearity, we obtain only local invariant manifolds no matter how large the spectral gap is unlike the deterministic cases. Based on these random dynamical systems, we prove the existence of random invariant manifolds in a tempered neighborhood of an equilibrium. Finally, we show that the images of these invariant manifolds under the inverse stationary transformation give invariant manifolds for the stochastic wave equations.     

Global Attractors for Multivalued Random Dynamical Systems Generated by Random Differential Inclusions with Multiplicative Noise

In this paper we consider a stochastic differential inclusion with multiplicative noise. It is shown that it generates a multivalued random dynamical system for which there also exists a global random attractor.