中立型随机泛函微分方程的稳定性

该文研究了一般中立型随机微分方程解的渐近性质,利用Lyapunov函数和上鞅收敛定理,得到 了该方程解的一些渐近稳定性、多项式渐近稳定性及指数稳定性等渐近性质,其结果涵盖并 推广了已有文献的结论。     

随机中立型泛函微分方程的稳定性态

给出了一类中立型随机泛函方程的随机一致稳定性的充分条件,利用了新的分析技巧处理中立型时滞项,得到了中立型随机时滞泛函微分方程渐近稳定性的充分判据.在处理各种渐近估计是有效的.     

一类两种群随机生态系统的稳定性

利用构造广义二次三项式作为随机李雅普诺夫函数的方法讨论了两种群随机Volterra生态系统的全局渐近稳定性，并对一类特殊情形给出了全局渐近稳定性的充分判据，推广了常微系统已有结果．     

带有延迟脉冲量的脉冲随机微分方程的稳定性（英文）

本文研究带有限延迟脉冲随机泛函微分方程的p阶矩稳定性和p阶矩渐近稳定性的问题.利用Razumikhin技巧和Lyapunov函数的方法,获得方程p阶矩稳定性和p阶矩渐近稳定性的结果.     

白噪声作用下统一混沌系统的脉冲同步

考察了白噪声和脉冲信号联合作用下统一混沌系统的随机渐近稳定性问题,得到该随机脉冲系统的比较系统,从而由该确定性比较系统的稳定性得到原随机脉冲系统的随机渐近稳定性.并从理论上得到能使该随机脉冲系统随机渐近稳定的参数取值范围,最后用数值仿真验证了理论结果的正确性.     

非线性随机Pantograph微分方程及其θ-方法的均方渐近稳定性

本文主要研究了非线性随机Pantograph微分方程,讨论了其零解的均方渐近稳定性并给出了零解均方渐近稳定的充分条件.在本文的第三部分,我们将随机θ-方法应用于这类问题,获得了数值解均方渐近稳定条件.     

随机泛函微分方程的渐近稳定性

应用多个Liapunov函数讨论了随机泛函微分方程解的渐近行为,建立了确定这种方程解的极限位置的充分条件,并且从这些条件得到了随机泛函微分方程渐近稳定性的有效判据,使实际应用中构造Liapunov函数更为方便．同时也说明了该结果包含了经典的随机泛函微分方程稳定性结果为其特殊情况．最后给出的结果在随机Hopfield神经网络中的应用．     

带马尔可夫跳的随机Hopfield神经网络的以分布渐近稳定性

讨论了带马尔可夫跳的随机Hopfield神经网络的以分布渐近稳定性.通过构造合适的Lyapunov函数,获得了判定带马尔可夫跳的随机Hopfield神经网络的以分布渐近稳定性的充分条件.     

基于马尔科夫和分数布朗运动具有扩散反应过程的随机基因调控网络模型

在考虑分数布朗运动,马尔可夫跳跃和时变时滞的扩散-反应过程的基础上建立了随机基因调控网络模型,通过构造Lyapunov函数,利用Wirtinger不等式和随机稳定性理论,时滞相关渐近稳定性定理,以推导线性矩阵不等式的形式实现了随机基因调控网络模型均方意义上的全局稳定性.     

一类随机离散Logistic时滞方程的渐近稳定性（英文）

本文提出了一类Logistic时滞模型的随机离散形式,并对其进行了研究.首先,讨论了相对应的确定性离散模型的稳定解.其次,在一些简单的条件下,证明了随机离散Logistic方程的渐近稳定性.最后,利用数值仿真说明了主要结果.     

Stochastic integrals of empirical-type processes with applications to censored regression

Motivated by the analysis of linear rank estimators and the Buckley-James nonparametric EM estimator in censored regression models, we study herein the asymptotic properties of stochastic integrals of certain two-parameter empirical processes. Applications of these results on empirical processes and their stochastic integrals to the asymptotic analysis of censored regression estimators are also given.     

随机时滞 Lotka-Volterra 模型

该文揭示了关于生物动态过程中的一类重要的模型, 随机时滞Lotka-Volterra模型的渐近行为, 这种随机过程的解具有很好的逼近性质:如, 解的轨道估计, 渐近性质, 而且它的解还具有随机有界性.     

Asymptotic mean-square stability of linear multi-step methods for SODEs

In this article we present results of a linear stability analysis of stochastic linear multi-step methods for stochastic ordinary differential equations. As in deterministic numerical analysis we use a linear time-invariant test equation and study when the numerical approximation shares asymptotic properties in the mean-square sense of the exact solution of that test equation. Sufficient conditions for asymptotic mean-square stability of stochastic linear two-step-Maruyama methods are obtained with the aide of Lyapunov-type functionals. In particular we study the asymptotic mean-square stability of stochastic counterparts of two-step Adams-Bashforth- and Adams-Moulton-methods and the BDF method. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Asymptotic Log-Harnack inequality and applications for stochastic systems of infinite memory

The asymptotic log-Harnack inequality is established for several kinds of models on stochastic differential systems with infinite memory: non-degenerate SDEs, neutral SDEs, semi-linear SPDEs, and stochastic Hamiltonian systems. As applications, the following properties are derived for the associated segment Markov semigroups: asymptotic heat kernel estimate, uniqueness of the invariant probability measure, asymptotic gradient estimate (hence, asymptotically strong Feller property), as well as asymptotic irreducibility.     

Stationary distribution and persistence of a stochastic predator-prey model with a functional response

A stochastic predator-prey model with a functional response is investigated in this paper. The asymptotic properties of the stochastic model are considered here. Under some conditions, we show that the stochastic model is persistent in mean. Moreover, the existence of stationary distribution to the model is obtained. Simulations are also carried out to confirm our analytical results.     

A note on the asymptotic distribution of the maximum likelihood estimator in a non-regular case

We consider the asymptotic distribution of the maximum likelihood estimator (MLE), when the log-likelihood ratio statistic weakly converges to the non-degenerated Gaussian process. We provide a simple expression for the density function of the asymptotic distribution by fundamental stochastic results. This note is helpful to investigate asymptotic properties of the MLE in a certain non-regular case.     

Markov调制的随机微分延迟方程的函数稳定性

随机微分延迟方程的指数稳定性被人们广泛研究,但讨论带Markov调制的随机微分延迟方程的函数稳定性的不多.本文主要研究了两种类型的函数稳定性.我们采用了一例特定的Lyapunov函数,来研究带Markov调制的随机微分延迟方程的p阶矩ψα-函数稳定性,并对其几乎必然ψβ/p-函数稳定性也进行了探讨.     

Asymptotic properties of neutral stochastic differential delay equations

This paper discusses asymptotic properties, especially asymptotic stability of neutral stochastic differential delay equations. New techniques are developed to cope with the neutral delay case, and the results of this paper are more general than the author's earlier work within the delay equations     

Random attractor of stochastic complex Ginzburg–Landau equation with multiplicative noise on unbounded domain

The existence of a compact random attractor for the stochastic complex Ginzburg–Landau equation with multiplicative noise has been investigated on unbounded domain. The solutions are considered in suitable spaces with weights. According to crucial properties of Ornstein–Uhlenbeck process, using the tail-estimates method, the key uniform a priori estimates for the tail of solutions have been obtained, which give the asymptotic compactness of random attractors. Then the existence of a compact random attractor for the corresponding dynamical system is proved in suitable spaces with weights.