摘要
树指标随机过程已成为近年来发展起来的概率论的研究方向之一.强偏差定理一直是国际概率论界研究的中心课题之一.本文通过构造适当的非负鞅,将Doob鞅收敛定理应用于几乎处处收敛的研究,研究给出了一类非齐次树上连续马氏信源熵密度的若干强偏差定理.
In recent years, tree indexed stochastic process has become one of the hot topics in probability theory. The strong deviation theorem has been one of the central issues of the international probability theory. In this paper, through constructing a non-negative martingale and applies Doob ~s martingale convergence theorem to the research of a. e. convergence, a class of strong deviation theorems of the entropy density of continuous Markov information source on a non-homogeneous tree are given.
出处
《大学数学》
2015年第3期1-6,共6页
College Mathematics
基金
河北省高等学校科学技术研究重点项目(ZD2014051)
关键词
非齐次树
鞅
马氏信源
强偏差定理
non-homogeneous tree
martingale, Markov information source
strong deviation theorem
