In order to plan ahead for multiple moves, an algorithm known as a markov decision process is commonly used when there are only a reasonably small group of possible world states.
为了计划后面多个步骤，当可能的世界状态数目不算太多时，通常用到一种被称作马尔科夫决策过程的算法。
A robot with only distance sensors cannot find its position in a symmetrical environment by means of Markov localization algorithm alone.
对只有距离传感器的机器人在对称的环境中仅仅采用该算法就无法确定位置。
This is a writer writing improvement of the people's hidden Markov model algorithm procedures.
这是一个笔者撰写改进了别人的隐马尔可夫模型算法的程序。
An algorithm for computing the stationary distribution of finite state discrete time Markov Chains is provided in the paper.
论文提出了一种计算有限状态离散时间马尔科夫链平稳分布的算法。
The experiments of Gauss Markov sequences show that the algorithm has better achieved the global optimal point and helps overcome the shortcoming of the sensitivity to initial codebook.
高斯·马尔科夫序列实验表明，该算法较好地实现了全局最优，并有助于克服对初始码书较为敏感的缺点。
This paper proposes a new algorithm using hidden Markov model for information extraction based on multiple templates due to the variety of training data.
针对训练数据来源的多样化，提出了基于多模板隐马尔可夫模型的文本信息抽取算法。
An average reward reinforcement learning algorithm for control Markov chains is presented.
讨论平均准则控制马氏链的强化学习算法。
Based on Markov analysis, this paper presents a recursive algorithm to compute probabilities under stable states and derives the approximate expression for order-based backorders.
通过马尔可夫分析，构造了求解系统处于平稳状态概率的迭代算法，提出了计算订单的平均缺货水平的近似表达式。
A fuzzy Markov random field (FMRF) model is established and a new algorithm based on FMRF for image segmentation proposed in this paper.
本文建立模糊马尔可夫场模型，并提出基于模糊马尔可夫场的图像分割新算法。
Methods: Based on Markov random fields model of noise, a iteration algorithm was presented by using maximum a posteriori (MAP) criterion.
方法：根据马尔科夫随机场图像模型，利用最大后验概率准则(MA P)，提出一种迭代松弛分割算法。
An algorithm generating Markov chain from heterogeneous software architecture modeled in UML sequence diagram is proposed.
基于软件UML顺序图，提出将异构软件结构转换为马尔可夫链的算法。
The algorithm makes use of the information of format and list separators to segment text, and then combines hidden Markov model for text information extraction.
该算法利用文本排版格式、分隔符等信息，对文本进行分块，在分块的基础上结合隐马尔可夫模型进行文本信息抽取。
A new algorithm based on hidden Markov Model is proposed for text information extraction.
提出了一种基于隐马尔可夫模型的文本信息抽取算法。
Absrtact: Document text images captured by book scanner or camera usually require resolution enhancement for other usage, present a text image enhancement algorithm based on Markov random field.
摘要：对于扫描或相机拍摄的低分辨率文本图片，提出一种基于马尔科夫随机场的文本图像清晰化算法。
The algorithm USES posterior information to modify model's noise variance and markov transition matrix, so as to make IMM have adaptive ability.
该算法采用后验信息修正模型的噪声方差和马尔可夫转移矩阵，使IMM具有自适应能力。
Secondly, taking the posterior probability as the target distribution, the Adaptive Metropolis algorithm was used to construct the Markov Chains of unknown parameters.
接着以后验概率分布为目标分布采用自适应Metropolis算法构造Markov链；
Then algorithm analysis of network traffic model, a brief introduction of the Poisson model, Markov model, ar, MA, ARMA model, focused on analyzing ARIMA model algorithm.
接着对网络流量模型算法分析，简单介绍了泊松模型，马尔科夫模型，AR,MA,ARMA模型，重点分析了ARIMA模型算法。
An abridged algorithm of 2d hidden Markov chain model and its parameter estimation method are made.
针对现有的二维隐马氏模型算法给出了一种简化算法及参数估计方法。
Then this thesis presents a new approach to solve top event occurrence rate and a new generation algorithm of minimal cut sequence of dynamic fault tree that deviate from Markov model completely.
提出了一种完全脱离马尔可夫模型的求解动态故障树顶事件发生概率的方法和一种最小顺序割集的生成方法。
This paper presents a novel unsupervised image segmentation algorithm based on hidden Markov random field(HMRF) model.
研究了基于隐马尔可夫随机场（HMRF）模型的无监督图像分割问题。
The mapped algorithm, called the Mahalanobis distance, handles about 50% of its computational load in the overall speech recognition algorithm using a continuous hidden Markov model(CHMM).
将基于连续隐含Markov模型语音识别算法中占系统总运算量的50%以上的Mahalanobis距离 计算，映射为硬件实现的 模块。
A new model based on Markov decision processes is proposed and the correlative novel algorithm is implemented with the adaptive ability of improved Q-learning for dynamic grid service selection.
对满足马尔可夫决策过程的服务组合提出了一种支持不完备信息描述的网格服务描述模型，实现了对服务组合整个生命周期的描述。
A new model based on Markov decision processes is proposed and the correlative novel algorithm is implemented with the adaptive ability of improved Q-learning for dynamic grid service selection.
对满足马尔可夫决策过程的服务组合提出了一种支持不完备信息描述的网格服务描述模型，实现了对服务组合整个生命周期的描述。
应用推荐