基于二维真实隐马氏模型的手写体文字识别算法

近几年来，人们采用各种方法试图将1D隐马氏模型(HMM)^[2]推广到2D隐马氏模型。令人失望的是由于在建立合适的2D模型及其计算上的复杂度问题上存在困难，前面的尝试都没有得到一个真实的2DHMM．本文对于应用真实2D隐马氏模型(隐马氏网格随机场HMMRF)^[1,4]进行手写字符识别问题提出新的框架，针对文献[1]中的单点最优算法给出局部最优的译码算法。HMMRF模型是1D隐马氏模型到2D的扩展，能更好的描述字符的2D特性。HMMRF在字符识别中的应用具有两个相——学习相和译码相。在学习相和译码相中我们的最优标准是基于极大边缘后验概率的。不过，在涉及到2D模型中的计算问题时，对模型做出某些简单化的假设是必要的。本文用到的方法对于在合理的模型假设下解决手写字符识别问题呈现了很大的潜力。     

Hidden Markov Filter Estimation of the Occurrence Time of an Event in a Financial Market

Abstract

In this paper, we use filtering techniques to estimate the occurrence time of an event in a financial market. The occurrence time is being viewed as a Markov stopping time with respect to the σ-field generated by a hidden Markov process. We also generalize our result to the Nth occurrence time of that event.     

Exponential bounds for convergence of entropy rate approximations in hidden Markov models satisfying a path-mergeability condition

A hidden Markov model (HMM) is said to have path-mergeable states   if for any two states i,j$i,j$ there exist a word w$w$ and state k$k$ such that it is possible to transition from both i$i$ and j$j$ to k$k$ while emitting w$w$. We show that for a finite HMM with path-mergeable states the block estimates of the entropy rate converge exponentially fast. We also show that the path-mergeability property is asymptotically typical in the space of HMM topologies and easily testable.     

马氏环境中马氏链的强大数定律

讨论了具有离散参数的马氏环境中马氏链的强大数定律，并给出了加在链和过程样本函数上的充分条件．同时深入研究了Rθ-链，得到马氏环境中马氏链强大数定律成立的充分条件．     

有限非齐次马氏链随机转移概率调和平均的一个强极限定理

设{X     

双无限环境中马氏链的强大数定律

在随机环境中马氏链的研究领域 ,构造了一时齐的马氏双链 ,讨论了它的存在性及基本性质 ,最后利用马氏双链的性质 ,得到了双无限环境中马氏链的函数极限定律 ,并给出了该链的函数强大数定律成立的两个充分条件     

The asymptotic equipartition property of Markov chains in single infinite Markovian environment on countable state space

ABSTRACT

The asymptotic equipartition property is a basic theorem in information theory. In this paper, we study the strong law of large numbers of Markov chains in single-infinite Markovian environment on countable state space. As corollary, we obtain the strong laws of large numbers for the frequencies of occurrence of states and ordered couples of states for this process. Finally, we give the asymptotic equipartition property of Markov chains in single-infinite Markovian environment on countable state space.     

基于灰色马尔可夫预测模型的农村人均收入预测

以武汉市农村人均收入为样本,将灰色预测模型和马尔可夫链预测模型相结合,通过对比预测的数据信息与实际数据信息差距,对2011年和2012年武汉市农村人均收入进行了预测计算.根据相关模拟检验与残差修正,灰色马尔可夫链可视为农村人均收入预测的可行且有效的方法.结果显示,单纯地运用灰色模型,预测值与实际值的误差均值是0.687%;通过马尔可夫链模型的二次模拟得到的误差明显减小.     

Design of trees in the hose model: The balanced case

In the hose model we are given upper bounds on the amount of traffic entering/leaving a node. We show that when , designing a minimum cost tree network is easy and the cost of an optimal tree reservation is within a factor of three of the cost of any reservation.     

价格贸易条件对经济增长影响的实证研究——基于混频数据马尔科夫区制转移模型

为研究不同经济增速状态下价格贸易条件对经济增速的影响,基于1994年1月至2018年12月的月度价格贸易条件及1994年1季度至2018年4季度的季度实际GDP增长率的混频数据,建立马尔科夫区制转移模型并进行实证分析.研究结果表明:在经济平稳增长状态,价格贸易条件情况改善对我国经济增速有正向影响.在经济快速增长状态,伴...     

The strong law of large numbers and the Shannon–McMillan theorem for nonhomogeneous Markov chains indexed by a Cayley tree

In this paper, we study the strong law of large numbers and the Shannon–McMillan theorem for nonhomogeneous Markov chains indexed by a Cayley tree. This article generalizes the relative results of level nonhomogeneous Markov chains indexed by a Cayley tree.     

基于马氏决策向量过程模型的有限阶段期望总报酬准则及其最优方程

在马氏决策向量过程模型的理论基础上,结合决策向量和相合度等新定义,进一步提出有限阶段期望总报酬准则和最优方程,并证明最优方程的解的存在性.     

Strong stability of the embedded Markov chain in an GI/M/1 queue with negative customers

This paper is devoted to the investigation for sufficient conditions of the strong stability of the embedded Markov chain in GI/M/1 queueing system with negative customers. After perturbing the occurrence rate of the negative customers, we prove the strong stability of the considered Markov chain with respect to a convenient weight variation norm. Furthermore, we estimate the deviation of its transition operators and provide an upper bound to the approximation error. This results allow us to understand how the negative customers will affect the system’s level of performance.     

The joint distributions of several important actuarial diagnostics in the classical risk model

In this paper we examine the joint distributions of several actuarial diagnostics which are important to insurers’ running in the classical risk model. They include the time of the surplus process leaving zero ultimately (simply, the ultimately leaving-time), the number of zero, the surplus immediately prior to ruin, the deficit at ruin, the supreme and minimum profits before ruin, the supreme profits and deficit until it leaves zero ultimately and so on. We obtain explicit expressions for their joint distributions mainly by strong Markov property of the surplus process—a technique used by Wu et al. (2002) [J. Appl. Math., in press], which is completely different from former contributions on this topic. Further, we give the exact calculating results for them when the individual claim amounts are exponentially distributed.     

Holdings of financial assets: A Markov chain analysis

This paper introduces the Markov chain model as a simple tool for analyzing the pattern of financial asset holdings over time. The model is based on transition probabilities which give the probability of switching $1 of wealth from one asset to another. An illustrative application is provided.     

加权马尔可夫链在传染病发病情况预测分析中的应用

首先基于传染病的发病情况存在大量不确定性的特点,应用有序聚类的方法建立发病人数状态的分级标准;然后针对发病人数序列为相依随机变量的特点,采取以规范化的各阶自相关系数为权重,用加权的马尔可夫链模型来预测和分析发病人数的变化状况,使预测结论的长期效果趋于最优;最后通过实例检验,对预测结果和方法进行评价和深入的分析.     

一类随机环境下马尔科夫链状态的分类

本文构造出具有两状态的一类平稳遍历的环境列下马尔科夫链的具体模型 ,并对该环境下马尔科夫链的相空间进行分解 .     

Bounds for the tail distribution in a queue with a superposition of general periodic Markov sources: theory and application

An efficient yet accurate estimation of the tail distribution of the queue length has been considered as one of the most important issues in call admission and congestion controls in ATM networks. The arrival process in ATM networks is essentially a superposition of sources which are typically bursty and periodic either due to their origin or their periodic slot occupation after traffic shaping. In this paper, we consider a discrete-time queue where the arrival process is a superposition of general periodic Markov sources. The general periodic Markov source is rather general since it is assumed only to be irreducible, stationary and periodic. Note also that the source model can represent multiple time-scale correlations in arrivals. For this queue, we obtain upper and lower bounds for the asymptotic tail distribution of the queue length by bounding the asymptotic decay constant. The formulas can be applied to a queue having a huge number of states describing the arrival process. To show this, we consider an MPEG-like source which is a special case of general periodic Markov sources. The MPEG-like source has three time-scale correlations: peak rate, frame length and a group of pictures. We then apply our bound formulas to a queue with a superposition of MPEG-like sources, and provide some numerical examples to show the numerical feasibility of our bounds. Note that the number of states in a Markov chain describing the superposed arrival process is more than 1.4 × 10⁸⁸. Even for such a queue, the numerical examples show that the order of the magnitude of the tail distribution can be readily obtained.     

Linear programming formulation of MDPs in countable state space: The multichain case

We present an Linear Programming formulation of MDPs with countable state and action spaces and no unichain assumption. This is an extension of the Hordijk and Kallenberg (1979) formulation in finite state and action spaces. We provide sufficient conditions for both existence of optimal solutions to the primal LP program and absence of duality gap. Then, existence of a (possibly randomized) average optimal policy is also guaranteed. Existence of a stationary average optimal deterministic policy is also investigated.