退化扩散过程小扰动的跑出分布估计

本文研究上的扩散过程，它是上退化扩散过程的小随机扰动，其中满足随机微分方程满足随机微分方程通过构造辅助系统，估计了的Freidlin-Wentzell型的跑出分布．     

噪声和生存环境对捕食生态系统的影响

建立了可以描述自然生物生存环境复杂度的捕食生态系统的随机模型,并基于实验得到的系统参数研究了生存环境复杂程度和随机激励强度对两个物种的稳态概率分布,以及系统由非临界状态到临界状态的平均首次穿越时间的影响．在弱扰动假设下应用Stratonovich-Khasminskii随机平均原理分别得到了两个物种的稳态概率密度函数并采用Monte-Carlo对原系统模拟来验证理论求解的正确性．利用Pontryagin方程得到了系统由非临界状态到临界状态的平均首次穿越时间表达式.研究表明:1)生存环境越简单的生态系统越容易受到随机因素的影响;2)随机干扰强度越大生态系统越不稳定;3)系统的平均首次穿越时间随生存环境复杂度提高而变长;4)作用在食物自然生长率的随机激励对系统的平均首次穿越时间影响较大．     

一个随机过程的小扰动的平均越出时间估计

考虑Ｒ＾ｄ（ｄ≥１）上随机过程｛Ｘ（ｔ）｝的小扰动｛Ｘ＾ε（Ｔ）｝,其中｛Ｘ（ｔ）｝和｛Ｘ＾ε（ｔ）｝分别满足随机微分方程ｄＸ（ｔ）＝ｂ（Ｘ（ｔ）,Ｚ（ｔ）ｄｔ和ｄＸ＾ε（ｔ）＝ｂ（Ｘ＾ε（Ｔ）,Ｚ（ｔ）ｄｔ＋εｄＢ（ｔ）,这里｛Ｚ（ｔ）｝是一个有限状态马氏过程,应用大偏差方法,给出了当扰动趋于零时,｛Ｘ＾ε（ｔ）｝是平均越出时间的渐近估计。     

Lur''e系统的扰动抑制分析

用不变集方法分析了有范数摄动的单输入单输出(SIS0)Lur′e系统持续有界扰动的抑制问题．通过Liapunov函数得到了用一组线性矩阵不等式(LMI)条件给出的扰动抑制和绝对稳定性结果．分析了这一条件的可行性，并用算例予以验证．还给出了鲁棒椭圆体吸引子的估计．     

三维随机Ising模型的亚稳态性(Ⅱ)

讨论三维格点环面上随机Ising模型当温度趋向零时的亚稳态性,确定从自旋全为-1的组态到自旋全为+1的组态的最大似然路径和临界组态,并计算出从自旋全为-1的组态出发首次到达自旋全为+1的组态的首达时间的渐近对数估计。证明利用一族带指数扰动的Markov链的大偏差估计。     

Meta回归模型的异常值识别及其修正

基于异常值对异质性参数和回归系数估计同时影响的这一新视角下,文章利用方差加权异常值模型(variance-weight outlier model,VWOM)研究了随机效应Meta回归模型的多个异常值识别及其修正问题。首先,推导出Meta回归VWOM分别使用ML和REML估计方法的Score (SC)检验统计量,并考虑Meta回归VWOM的三种扰动方式,包括全局方差扰动,个体方差扰动和随机误差扰动,证明了三种方差扰动的SC检验统计量是等价的。其次,基于异常值对异质性参数和回归系数估计同时影响的考虑,提出了随机效应Meta回归方差加权异常值修正模型(variance-weight outlier modified model,VWOMM),并给出了VWOMM参数的ML和REML估计迭代算法并进行数值求解。此外,通过随机模拟分析验证了SC检验统计量的尺度和功效。最后,利用两个不同类型效应量异常值识别及其处理的实例分析结果,表明了Meta回归VWOM的SC检验统计量识别效果较为显著,VWOMM能有效改善模型拟合程度,为识别和处理复杂数据的异常值提供了一种新的思路和方法。     

后继函数法与 Bogdanov-Takens 系统的二次扰动

本文利用后继函数法和隐函数定理,并结合Mel’nikov函数的计算,对Bogdanov-Takens系统在二次扰动下从中心分岔出的极限环个数进行了估计．     

一类扰动多项式系统极限环

本文对一类多项式扰动系统的极限环进行了研究，得到了极限环个数的上界估计，弥补了文献［２］主要定理的不足．     

方差可能无穷的“中度偏离”单位根过程的复合分位数估计

考虑一类"中度偏离"单位根过程,y_t=q_ny_t-1+u_t,其中qn=1+c/(k_n),k_n=o(n),c为一非零常数,{u_t}为随机扰动项序列.在允许扰动项方差无穷的条件下,构造q_n的复合分位数估计,并得到了该估计的渐近分布.最后通过数值模拟,在扰动项服从t(2)分布下,说明了该估计的稳健和有效性.     

12参双参数矩形板元的误差估计

双参数方法是构造高阶问题有限元的有效方法．以此方法构造的双参数元是一种非标准元，以往文献中只证明了它的收敛性．此文针对具体12参双参数矩形板元给出它的误差估计式，并分析了节点参数的扰动量．文中的分析方法也适合于其它双参数矩形板元的误差估计．     

Small random perturbations of one-dimensional diffusion processes

In the present paper we consider the small random perturbations of one-dimensional diffusion processes. By virtue of stochastic analysis methods, we investigate the asymptotics of the mean exit times and probabilistical estimates of the exit times as the perturbations tend to zero. Partially supported by the Young Teachers Foundation of Beijing Institute of Technology     

The Poincaré Map of Randomly Perturbed Periodic Motion

A system of autonomous differential equations with a stable limit cycle and perturbed by small white noise is analyzed in this work. In the vicinity of the limit cycle of the unperturbed deterministic system, we define, construct, and analyze the Poincaré map of the randomly perturbed periodic motion. We show that the time of the first exit from a small neighborhood of the fixed point of the map, which corresponds to the unperturbed periodic orbit, is well approximated by the geometric distribution. The parameter of the geometric distribution tends to zero together with the noise intensity. Therefore, our result can be interpreted as an estimate of the stability of periodic motion to random perturbations. In addition, we show that the geometric distribution of the first exit times translates into statistical properties of solutions of important differential equation models in applications. To this end, we demonstrate three distinct examples from mathematical neuroscience featuring complex oscillatory patterns characterized by the geometric distribution. We show that in each of these models the statistical properties of emerging oscillations are fully explained by the general properties of randomly perturbed periodic motions identified in this paper.     

Scaling limit for the diffusion exit problem in the Levinson case

The exit problem for small perturbations of a dynamical system in a domain is considered. It is assumed that the unperturbed dynamical system and the domain satisfy the Levinson conditions. We assume that the random perturbation affects the driving vector field and the initial condition, and each of the components of the perturbation follows a scaling limit. We derive the joint scaling limit for the random exit time and exit point. We use this result to study the asymptotics of the exit time for 1D diffusions conditioned on rare events.     

Global well-posedness for the KP-II equation on the background of a non-localized solution

Motivated by transverse stability issues, we address the time evolution under the KP-II flow of perturbations of a solution which does not decay in all directions, for instance the KdV-line soliton. We study two different types of perturbations: perturbations that are square integrable in R×T and perturbations that are square integrable in R². In both cases we prove the global well-posedness of the Cauchy problem associated with such initial data.     

Exit times for multivariate autoregressive processes

We study exit times from a set for a family of multivariate autoregressive processes with normally distributed noise. By using the large deviation principle, and other methods, we show that the asymptotic behavior of the exit time depends only on the set itself and on the covariance matrix of the stationary distribution of the process. The results are extended to exit times from intervals for the univariate autoregressive process of order n$n$, where the exit time is of the same order of magnitude as the exponential of the inverse of the variance of the stationary distribution.     

Multiscale analysis of exit distributions for random walks in random environments

We present a multiscale analysis for the exit measures from large balls in , of random walks in certain i.i.d. random environments which are small perturbations of the fixed environment corresponding to simple random walk. Our main assumption is an isotropy assumption on the law of the environment, introduced by Bricmont and Kupiainen. Under this assumption, we prove that the exit measure of the random walk in a random environment from a large ball, approaches the exit measure of a simple random walk from the same ball, in the sense that the variational distance between smoothed versions of these measures converges to zero. We also prove the transience of the random walk in random environment. The analysis is based on propagating estimates on the variational distance between the exit measure of the random walk in random environment and that of simple random walk, in addition to estimates on the variational distance between smoothed versions of these quantities. Partially supported by NSF grant DMS-0503775.     

Moderate deviations for randomly perturbed dynamical systems

A Moderate Deviation Principle is established for random processes arising as small random perturbations of one-dimensional dynamical systems of the form X_n=f(X_n−1). Unlike in the Large Deviations Theory the resulting rate function is independent of the underlying noise distribution, and is always quadratic. This allows one to obtain explicit formulae for the asymptotics of probabilities of the process staying in a small tube around the deterministic system. Using these, explicit formulae for the asymptotics of exit times are obtained. Results are specified for the case when the dynamical system is periodic, and imply stability of such systems. Finally, results are applied to the model of density-dependent branching processes.     

Estimates for first exit times of non-Markovian Itô processes

First exit times and their path-wise dependence on trajectories are studied for non-Markovian Itô processes. Estimates of distances between two exit times are obtained. In particular, it follows that first exit times of two Itô processes are close if their trajectories are close.     

On the dimension of the subspace of Liouvillian solutions of a Fuchsian system

The effect of small constantly acting random perturbations of white noise type on a dynamical system with locally stable fixed point is studied. The perturbed system is considered in the form of Itô stochastic differential equations, and it is assumed that the perturbation does not vanish at a fixed point. In this case, the trajectories of the stochastic system issuing from points near the stable fixed point exit from the neighborhood of equilibrium with probability 1. Classes of perturbations such that the equilibrium of a deterministic system is stable in probability on an asymptotically large time interval are described.