Non-Recursive Base Conversion Using a Deterministic Markov Process

We prove that non-recursive base conversion can always be implemented by using a deterministic Markov process. Our paper discusses the pros and cons of recursive and non-recursive methods, in general. And we include a comparison between non-recursion and a deterministic Markov process, proving that the Markov process is twice as efficient.

Exponential stability of impulsive jump linear systems with Markov process

The exponential stability is investigated for a class of continuous time linear systems with a finite state Markov chain form process and the impulsive jump at switching moments. The conditions, based on the average dwell time and the ratio of expectation of the total time running on all unstable subsystems to the expectation of the total time running on all stable subsystems,assure the exponential stability with a desired stability degree of the system irrespective of the impact of impulsive jump. The uniformly bounded result is realized for the case in which switched system is subjected to the impulsive effect of the excitation signal at some switching moments.

THE EQUILIBRIUM PROBLEM AND CAPACITY FOR JUMP MARKOV PROCESSES

Let X=(Omega,F,F-t,X(t),theta(t),P-x) be a jump Markov process with q-pair q(x)-q(x, A). In this paper, the equilibrium principle is established and equilibrium functions, energy, capacity and related problems is investigated in terms of the q-pair q(x)-q(x, A).

MOMENTS OF PASSAGE TIMES AND ASYMPTOTIC BEHAVIOR OF INCREASING SELF-SIMILAR MARKOV PROCESSES

By using Lamperti＇s bijection between self-similar Markov processes and L@vy processes~ we prove finiteness of moments and asymptotic behavior of passage times for increasing self-similar Markov processes valued in （0, ~）. We Mso investigate the behavior of the process when it crosses a level. A limit theorem concerning the distribution of the process immediately before it crosses some level is proved. Some useful examples are given.

Seismic response evaluation of the impact of corrosion on buried pipelines based on the Markov process

Water distribution and gas supply systems are among the infrastructure systems that have many buried steel pipelines. Corrosion gradually appears inside and outside of the pipe walls over the service life of these pipelines, the corrosion is primarily caused by the surrounding soil and the materials that flow through the pipelines. However, due to the uncertainty of the characteristics of the soil and materials, the size of the corrosion region is a stochastic variable. In this paper, using a homogeneous Markov process, a model is presented to simulate the occurrence of corrosion. Then, in combinations with a linear corrosion development model, the probability density function of the pipeline area corrosion percentage is derived. Based on the corrosion model, the pipeline seismic displacements and stresses are predicted. Furthermore, using the random perturbation approach, the mean and variance of the pipeline seismic response are given. To illustrate the validity of the proposed approach, a 200-meter long pipeline is numerically investigated and its random seismic response is obtained.

Asymptotic Evaluations of the Stability Index for a Markov Control Process with the Expected Total Discounted Reward Criterion

In this work, for a control consumption-investment process with the discounted reward optimization criteria, a numerical estimate of the stability index is made. Using explicit formulas for the optimal stationary policies and for the value functions, the stability index is explicitly calculated and through statistical techniques its asymptotic behavior is investigated (using numerical experiments) when the discount coefficient approaches 1. The results obtained define the conditions under which an approximate optimal stationary policy can be used to control the original process.

Definition of Laplace Transforms for Distribution of the First Passage of Zero Level of the Semi-Markov Random Process with Positive Tendency and Negative Jump

One of the important problems of stochastic process theory is to define the Laplace transforms for the distribution of semi-markov random processes. With this purpose, we will investigate the semimarkov random processes with positive tendency and negative jump in this article. The first passage of the zero level of the process will be included as a random variable. The Laplace transforms for the distribution of this random variable is defined. The parameters of the distribution will be calculated on the basis of the final results.

具有变时滞Markov跳跃神经网络的H∞控制

文章研究了具有变时滞Markov跳跃神经网络的H∞控制。首先,设计一个输出反馈控制器,以确保Markov跳跃神经网络系统在没有外部扰动的情况下随机稳定,并在零初始条件下具有规定的干扰衰减指标。其次,利用适当的泛函和几个先进不等式获得所需控制器增益的精确数学表达式。最后,通过数值模拟的例子证明所提控制策略的有效性。

基于Markov过程的继电保护通信系统可靠性评估方法

继电保护通信系统受内外部因素影响,易出现拒动失效。传统评估方法未充分考虑动态行为、故障传播及复杂环境,导致评估结果中拒动失效率偏高。因此,文章提出基于Markov过程的继电保护通信系统可靠性评估方法。通过选取合适的可靠性评估指标全面反映系统的性能特点,利用Markov过程构建状态随机转移概率矩阵,描述系统在不同状态下的转移概率,综合评估继电保护通信系统的可靠性。实验结果表明,该方法综合考虑多种因素,拒动失效率较低,为电力系统的安全稳定运行提供有力支持。

Availability analysis of private cloud safety computer platform based on the Markov process

To ensure the correctness of train control system design and development,the ways of simulation,test and formalization were compared.According to the safe critical attribute of train control system,the characters related to system safety were propounded such as real time,hybrid,distribution(concurrence)and reactivity,and the specific formal methods associated with every character were introduced in details.The analysis and classification of the methods were done based on their mathematical basis and applications,and their advantages and disadvantages were given.Analysis result indicates that every method has determinate limitations,which is determined by the essences of model checking and theory proving.It is pointed out that the presentation of new method,the expansion of existing methods and the integration of many methods will be the development trend of formalization in train control system.

Markov process functionals in finance and insurance

The Markov property of Markov process functionals which are frequently used in economy, finance, engineering and statistic analysis is studied. The conditions to judge Markov property of some important Markov process functionals are presented, the following conclusions are obtained： the multidimensional process with independent increments is a multidimensional Markov process; the functional in the form of path integral of process with independent increments is a Markov process; the surplus process with the doubly stochastic Poisson process is a vector Markov process. The conditions for linear transformation of vector Markov process being still a Markov process are given.

Modeling and Design of Real-Time Pricing Systems Based on Markov Decision Processes

A real-time pricing system of electricity is a system that charges different electricity prices for different hours of the day and for different days, and is effective for reducing the peak and flattening the load curve. In this paper, using a Markov decision process (MDP), we propose a modeling method and an optimal control method for real-time pricing systems. First, the outline of real-time pricing systems is explained. Next, a model of a set of customers is derived as a multi-agent MDP. Furthermore, the optimal control problem is formulated, and is reduced to a quadratic programming problem. Finally, a numerical simulation is presented.

数字化前后人民币汇率动态特征和路径转变分析——基于三机制Markov转换模型

通过邹氏断点检验建立人民币/美元汇率的三机制Markov转换自回归模型,选取2019年6月25日—2021年4月30日的人民币/美元汇率数据,将2020年5月29日作为人民币数字化的节点,实证分析数字人民币发展前后两个阶段的汇率机制转换特征;采用主观层次分析法计算数字人民币对当前金融体系各项指标的影响权重,分析数字人民币的发展对当前金融体系的影响程度。结果表明:数字人民币推进前,汇率在各机制上停留时间具有连续性,且均表现出高度“自维持性”;数字人民币推进后,汇率的动态转换较频繁,对外部信息冲击的反映较强烈。数字人民币进程的稳步推进对当前金融体系各方面带来不同程度的影响,对汇率的影响较明显。

SMALL PERTURBATION CRAMER METHODS AND MODERATE DEVIATIONS FOR MARKOV PROCESSES

This paper presents a small perturbation Cramer method for obtaining the large deviation principle of a family of measures (β,ε> 0) on a topological vector space. As an application, we obtain the moderate deviation estimations for uniformly ergodic Markov processes.

Robust H_∞ Control for Uncertain Markovian Jump Linear Time-Delay Systems

This paper studies the robust stochastic stabilization and robust H∞ control for linear time-delay systems with both Markovian jump parameters and unknown norm-bounded parameter uncertainties. This problem can be solved on the basis of stochastic Lyapunov approach and linear matrix inequality (LMI) technique. Sufficient conditions for the existence of stochastic stabilization and robust H∞ state feedback controller are presented in terms of a set of solutions of coupled LMIs. Finally, a numerical example is included to demonstrate the practicability of the proposed methods.

改进的Markov和联合密度特征的MP3隐写分析方法

提出了一种MDCT(修正的离散余弦变换)域的MP3隐写分析方法。该方法通过改进的Markov特征集和联合密度特征集提取出MDCT系数的特征,经过方差分析选择有效的特征用于支持向量机(SVM)的训练与检测。实验结果表明,与以往方法相比提高了对MP3Stego的检测率,能有效地检测常见的MDCT系数修改的MP3信息隐藏方法。

Convergence of Invariant Measures of Truncation Approximations to Markov Processes

Let Q be the Q-matrix of an irreducible, positive recurrent Markov process on a countable state space. We show that, under a number of conditions, the stationary distributions of the n × n north-west corner augmentations of Q converge in total variation to the stationary distribution of the process. Two conditions guaranteeing such convergence include exponential ergodicity and stochastic monotonicity of the process. The same also holds for processes dominated by a stochastically monotone Markov process. In addition, we shall show that finite perturbations of stochastically monotone processes may be viewed as being dominated by a stochastically monotone process, thus extending the scope of these results to a larger class of processes. Consequently, the augmentation method provides an attractive, intuitive method for approximating the stationary distributions of a large class of Markov processes on countably infinite state spaces from a finite amount of known information.

ON THE HITTING PROBABILITY AND POLARITY FOR A CLASS OF SELF-SIMILAR MARKOV PROCESSES

The anthem investigate the hitting probability, polarity and the relationship between the polarity and Hausdorff dimension for self-similar Markov processes with state space (0, infinity) and increasing path.

MARKOV SKELETON PROCESS IN PERT NETWORKS

In this article, we investigate Programming Evaluation and Review Technique networks with independently and generally distributed activity durations. For any path in this network, we select all the activities related to this path such that the completion time of the sub-network （only consisting of all the related activities） is equal to the completion time of this path. We use the elapsed time as the supplementary variables and model this sub-network as a Markov skeleton process, the state space is related to the subnetwork structure. Then use the backward equation to compute the distribution of the sub-network＇s completion time, which is an important rule in project management and scheduling.

Wind power time series simulation model based on typical daily output processes and Markov algorithm

The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind power at each moment;however,they ignore the daily output characteristics and are unable to consider both modeling accuracy and efficiency.To resolve this problem,a wind power time series simulation model based on typical daily output processes and Markov algorithm is proposed.First,a typical daily output process classification method based on time series similarity and modified K-means clustering algorithm is presented.Second,considering the typical daily output processes as status variables,a wind power time series simulation model based on Markov algorithm is constructed.Finally,a case is analyzed based on the measured data of a wind farm in China.The proposed model is then compared with traditional methods to verify its effectiveness and applicability.The comparison results indicate that the statistical characteristics,probability distributions,and autocorrelation characteristics of the wind power time series generated by the proposed model are better than those of the traditional methods.Moreover,modeling efficiency considerably improves.