Description: HMM源码的简单版，隐马氏过程，概率及数理统计中的模型，可用于图像识别。-HMM-source version of the simple, Hidden Markov processes, probability and mathematical statistics in the model, can be used for image recognition. Platform: |
Size: 727040 |
Author:shuihemumumu |
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Description: 在现有的单层马尔科夫链异常检测模型基础上,提出一种崭新的两层模型.将性质上有较大差异的两个过程,不同的请求和同一请求内的系统调用序列,分为两层,分别用不同的马尔可夫链来处理.两层结构可以更准确地刻画被保护服务进程的动态行为,因而能较大地提高异常的识别率,降低误警报率.-In the existing single-layer Markov chain model for anomaly detection based on a new two-tier model. Will have a larger difference in the nature of the two processes, different requests and requests within the same system call sequence, sub- for a two-tier, respectively, in different Markov chain to deal with it. a two-tier structure can be more accurately portray the process of protection services by the dynamic behavior, which can greatly improve the identification of abnormal rate and reduce false alarm rate. Platform: |
Size: 356352 |
Author:杨奇 |
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Description: Markov参数是系统能观测性规范型实现时的重要参数，他给出了系统能观测性规范型的一种简单的实现方法。给出了Markov参数的定义、算法流程及运行算例，最后给出源程序！-Markov parameter is the system to standardize the type of observation when the realization of the important parameters, he gives the observation system can standardize the type of a simple method. Given the definition of Markov parameters, the algorithm processes and run an example, given the source code! Platform: |
Size: 23552 |
Author:yzy |
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Description: Depth Map Calculation for a Variable Number of Moving Objects Using Markov Sequential Object Processes Platform: |
Size: 632832 |
Author:孟钢 |
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Description: 马尔可夫过程是一类重要的随机过程,它的原始模型马尔可夫链,由俄国数学家Α.Α.马尔可夫于1907年提出。本程序是对隐马尔可夫模型的一个完整的建模。 -Markov process is one important class of stochastic processes, and its original model of Markov chain, by the Russian mathematician Markov Α.Α. made in 1907. This procedure is a Hidden Markov Model of a complete modeling. Platform: |
Size: 206848 |
Author:lili |
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Description: 该程序实现半隐式马尔可夫模型。对于通信工作者以及对随机过程研究者有用。希望大家喜欢。-The program realization of semi-hidden Markov model. For the communication workers and researchers on the usefulness of stochastic processes. Hope everyone likes. Platform: |
Size: 1024 |
Author:刘红 |
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Description: a book chapter about Markov Chains-Introduction
Most of our study of probability has dealt with independent trials processes. These
processes are the basis of classical probability theory and much of statistics. We
have discussed two of the principal theorems for these processes: the Law of Large
Numbers and the Central Limit Theorem. Platform: |
Size: 361472 |
Author:Chris Leung |
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Description: 《Software for Flexible Bayesian Modeling and Markov Chain Sampling》是机器学习领域专家Neal编写的用于Bayesian和马尔可夫链Linux下的C语言工具包。很有名，也很权威。
-This software supports Bayesian regression and classification models based on neural networks and Gaussian processes, and Bayesian density estimation and clustering using mixture models and Dirichlet diffusion trees. It also supports a variety of Markov chain sampling methods, which may be applied to distributions specified by simple formulas, including simple Bayesian models defined by formulas for the prior and likelihood. Platform: |
Size: 974848 |
Author:王磊 |
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Description: 西安电子科技大学研究生学院随机过程课件（宋月版），每一章都很详细。主要内容为：概率论基础、随机分析、平稳过程、马尔科夫过程-Xi' an University of Electronic Science and Technology Graduate School of stochastic processes courseware (Song month version), each chapter is very detailed. The main contents are: the basis of probability theory, stochastic analysis, stationary processes, Markov processes Platform: |
Size: 2614272 |
Author: |
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Description: 本书从简单的例子开始 ,介绍了马尔可夫决策过程的基本概念、决策过程以及一些常用 的基本理论 .还介绍了多种最优准则 , 包括有限阶段准则、折扣准则、平均准则、权重报酬准 则、概率准则等 .从模型角度考虑了有限状态空间、可数状态空间和一般 Borel 状态空间 从 决策时间上来说 , 考虑了离散时间、连续时间和半马氏决策时刻问题 .本文还介绍了大量的应 用实例以及建模方法 .本书可作为高年级大学生和研究生教材 , 也可作为运筹学、管理科学、 信息科学、系统科学以及计算机科学和工程领域的学者和技术人员的参考书 .
-From the simple example of this book introduces the basic concepts of Markov decision processes, and decision-making process as well as some common basic theory also describes the various optimal criteria, including criteria for limited stage, discounted, average criteria weights remuneration The guidelines, such as the probability criterion from the point of view of the finite state model space countable state space and general Borel state space from the decision-making time, consider a discrete-time, continuous-time and half-time Markov decision problem this article describes. a large number of application examples and modeling methods. book can serve as senior undergraduate and graduate teaching, but also as research, reference management science, information science, system science, and academics and technical staff in computer science and engineering fields. Platform: |
Size: 1283072 |
Author:何鹏飞 |
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Description: 马尔可夫过程的介绍与应用的电子书籍，现实世界中的很多过程都可假定为马尔可夫过程，其数学模型广泛应用于科学研究中。-Markov process of introduction and application of e-books, many of the processes in the real world can be assumed to be a Markov process whose mathematical model is widely used in scientific research. Platform: |
Size: 12410880 |
Author:w |
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Description: Hidden Markov modelling of contourlet transforms for art authentication
Bayesian robust hidden Markov model
Hidden Markov Models for Molecular Motors
When wavelet meet HMM
Hidden Markov Tree model of Contourlet Transform
EM for HMM Multivariate Gaussian processes
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Size: 957440 |
Author:amin |
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Description: 物理马尔可夫链通常用来建模排队理论和统计学中的建模，还可作为信号模型用于熵编码技术，如算术编码（著名的LZMA数据压缩算法就使用了马尔可夫链与类似于算术编码的区间编码）。马尔可夫链也有众多的生物学应用，特别是人口过程，可以帮助模拟生物人口过程的建模。隐蔽马尔可夫模型还被用于生物信息学，用以编码区域或基因预测-Physical Markov chains are typically used to model queuing theory and statistics in modeling, but also as a signal model for entropy coding techniques such as arithmetic coding (famous LZMA data compression algorithm on the use of Markov chain and similar in arithmetic coding interval encoding). Markov chains also have many biological applications, particularly population processes, can help the process simulation modeling biological populations. Hidden Markov models are also used bioinformatics to the coding region or gene prediction Platform: |
Size: 1024 |
Author:肖聪 |
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Description: 用于有限状态的半马尔柯夫过程的理论、建模计算及应用(This book aims to give a complete and self-contained presentation of
semi-Markov processes with finitely many states, divided into three major
topics: theory, computation, and application in a correct approach for
building applied stochastic models.) Platform: |
Size: 10147840 |
Author:张玉 |
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