非时齐马氏过程的对数Sobolev不等式

本文将时齐马氏过程的经典对数Sobolev不等式推广到非时齐马氏过程,建立了非时齐马氏过程的转移半群与对数Sobolev不等式之间的关系.     

非时齐Markov过程的Nash不等式

本文将时齐Markov过程的经典Nash不等式推广到非时齐Markov过程,建立了非时齐Markov过程的转移半群与Nash不等式之间的关系.     

非时齐马氏过程的随机单调性

本文研究了非时齐马氏过程的随机单调性问题.利用时齐的马氏过程随机单调性的相关证明方法,加以改进,获得了非时齐马氏过程随机单调性的显式判定方法,并进一步将这一充分性条件推广为等价条件.     

泛函不等式及其应用

本文介绍有关泛函不等式及谱理论与马氏过程研究的若干新进展，我们首先简要回顾了两个著名不等式，即Poincare不等式与对数不等式，然后分别使用泛函不等式研究本征谱、马氏半群的收敛速度和运费不等式．     

非时齐马氏过程的耦合基本定理

本文将耦合方法应用于非时齐马氏过程,推广了时齐情形的耦合基本定理,为后续研究非时齐马氏过程的耦合提供了理论基础.     

非时齐准转移函数及其所对应的两个单参数半群

众所周知，由于双参数半群的局限，使得对时齐马氏过程的许多结果无法在非时齐马氏过程得到，或得到的结果也较时齐的情况粗糙得多．本文给出了与非时齐准转移函数对应的两个单参数半群，研究了二者的性质，并证明了二者相互唯一决定。这就提供了一条由单参数压缩半群研究非时齐马氏过程的途径。     

一个非时齐马氏过程

<正> 本文研究了一个非时齐马氏过程,考虑其瞬时性质与渐近性质.过程的实际背景是成批到来无限束的 M(t)/M(t)/∞排队问题,排队过程的到来的强度,批量的大小与服务的强度均随时间变化.§1.引言由于实践范围的扩大,若干重要马氏过程的非时齐情况在近年来都得到深入研究.本文旨在考虑一个出现于排队论中的非时齐马氏过程 (在排队论中非时齐过程的重要性早已在[2]中指出过).     

用概率距离研究非时齐马氏链的收敛性

该文用概率距离和耦合方法研究了一般状态空间非时齐马氏链的收敛性,得到了一般状态空间.非时齐马氏链收敛的一个条件.     

一类索赔为马氏链的风险模型

本文研究了索赔为马氏链的离散风险模型.利用鞅方法得到破产概率的Lundberg不等式,并且给出了当索赔为独立同分布时的Lundberg不等式.     

利率为马氏链的离散时间风险模型的破产概率(英文)

本文考虑了带随机利率的离散时间风险模型.在假设利率为马氏链条件下,得到了有限时间和最终破产概率所满足的递推积分方程,以及最终破产概率的Lundberg不等式.     

Semi-linear problems in infinite dimensions

We prove existence, smoothness and ergodicity results for semilinear parabolic problems on infinite dimensional spaces assuming the Logarithmic Sobolev inequality is satisfied. As a consequence we construct a class of nonlinear Markov semigroup which are hypercontractive.     

$\boldsymbol{\mathcal{G}-}$Inhomogeneous Markov Systems of High Order

In the present, we introduce and study the G-\mathcal{G-}inhomogeneous Markov system of high order, which is a more general in many respects stochastic process than the known inhomogeneous Markov system. We define the inhomogeneous superficial razor cut mixture transition distribution model extending for the homogeneous case the idea of the mixture transition model. With the introduction of the appropriate vector stochastic process and the establishment of relationships among them, we study the asymptotic behaviour of the G-\mathcal{G-}inhomogeneous Markov system of high order. In the form of two theorems, the asymptotic behaviour of the inherent G-\mathcal{G-}inhomogeneous Markov chain and the expected and relative expected population structure of the G-\mathcal{G-}inhomogeneous Markov system of high order, are provided under assumptions easily met in practice. Finally, we provide an illustration of the present results in a manpower system.     

On optimal stopping of inhomogeneous standard Markov processes

The connection between the optimal stopping problems for inhomogeneous standard Markov process and the corresponding homogeneous Markov process constructed in the extended state space is established. An excessive characterization of the value-function and the limit procedure for its construction in the problem of optimal stopping of an inhomogeneous standard Markov process is given. The form of -optimal (optimal) stopping times is also found.     

Derivatives of Faber Polynomials and Markov Inequalities

We study asymptotic behavior of the derivatives of Faber polynomials on a set with corners at the boundary. Our results have applications to the questions of sharpness of Markov inequalities for such sets. In particular, the found asymptotics are related to a general Markov-type inequality of Pommerenke and the associated conjecture of Erd s. We also prove a new bound for Faber polynomials on piecewise smooth domains.     

Lyapunov conditions for Super Poincaré inequalities

We show how to use Lyapunov functions to obtain functional inequalities which are stronger than Poincaré inequality (for instance logarithmic Sobolev or F-Sobolev). The case of Poincaré and weak Poincaré inequalities was studied in [D. Bakry, P. Cattiaux, A. Guillin, Rate of convergence for ergodic continuous Markov processes: Lyapunov versus Poincaré, J. Funct. Anal. 254 (3) (2008) 727-759. Available on Mathematics arXiv:math.PR/0703355, 2007]. This approach allows us to recover and extend in a unified way some known criteria in the euclidean case (Bakry and Emery, Wang, Kusuoka and Stroock, …).     

Coupling, convergence rates of Markov processes and weak Poincaré inequalities

Some analytic and probabilistic properties of the weak Poincaré inequality are obtained. In particular, for strong Feller Markov processes the existence of this inequality is equivalent to each of the following: (i)the Liouville property (or the irreducibility); (ii) the existence of successful couplings (or shift-couplings); (iii)the convergence of the Markov process in total variation norm; (iv) the triviality of the tail (or the invariant)σ-field; (v) the convergence of the density. Estimates of the convergence rate in total variation norm of Markov processes are obtained using the weak Poincaré inequality.     

Coupling, convergence rates of Markov processes and weak Poincaré inequalities

Some analytic and probabilistic properties of the weak Poincaré inequality are obtained. In particular, for strong Feller Markov processes the existence of this inequality is equivalent to each of the following: (i) the Liouville property (or the irreducibility); (ii) the existence of successful couplings (or shift-couplings); (iii) the convergence of the Markov process in total variation norm; (iv) the triviality of the tail (or the invariant) σ-field; (v) the convergence of the density. Estimates of the convergence rate in total variation norm of Markov processes are obtained using the weak Poincaré inequality     

Recent Results on Recurrent Solutions and Limit Distributions of SDEs

The limit distribution for homogeneous Markov processes is studied extensively and well understood, but it is not the case for inhomogeneous Markov processes. In this paper, we review some recent results on inhomogeneous Markov processes generated by non-autonomous stochastic (partial) differential equations (SDE in short). Under some suitable conditions, we show that the distribution of recurrent solutions of SDEs constitutes the limit distribution of the corresponding inhomogeneous Markov processes.     

Déviations modérées pour la moyennisation d'une EDS avec petite diffusion

We prove in this Note the moderate deviation principle (MDP) for the averaging principle of a stochastic differential equation (SDE) in a fast random environment, modelized by an exponentially ergodic Markov process independent of the Wiener process driving the SDE. The main tools will be the method of Puhalskii for exponential tightness and a MDP for inhomogeneous functionals of Markov processes established in [5].