A wavelet domain hidden markov tree ( hmt ) model is constructed to model statistical dependence and nongaussian statistics of wavelet coefficient . the estimate of hmt model parameters can be obtained by em algorithm 该方法通过小波域的隐markov树（ hmt ）模型来描述小波系数的统计相关性和非高斯性，利用em算法获得hmt模型参数的估计。
So we use blob - matching algorithm to get motion parameters and make use of em algorithm to classify these parameters . these algorithms do not use optical flow computation and affine transformation , so it smoothes the difficulty of calculation 本文采用em算法直接对块匹配求得的运动参数进行分类,绕开光流计算和仿射变换,减小了计算量。
In this article , we apply em algorithm to estimating the values of the parameters of nhpp models . the estimating accuracy may be increased by this way . so the result software reliability analysis may be improved by this way too 最后本文应用文献[ 33 ]中介绍的em算法于nhpp类模型的参数估计,以提高估计的精度,从而提高软件可靠性分析的精确程度。
It follows from the general convergence theory that the em algorithm generally converge to a local maximum solution of the likelihood function and cannot be guaranteed to converge to a correct solution , i . e . , a consistent solution of the samples Em算法的一般收敛理论认为，算法只能收敛到似然函数的一个局部极大解，无法保证能够收敛到与样本的真实参数相一致的解上。
The distribution of mixture of densities is very popular in practice and the data subject to such a distribution can be viewed as a kind of incomplete data . so , the em algorithm for mixtures of densities , particularly for gaussian mixtures , is very important 由于概率混合体分布在实际应用中相当普遍并且服从于它的数据可以看作是一种不完全数据，依此建立的em算法一直受到人们的重视，特别是高斯混合体em算法。
Obtain the conclusion that em algorithm is better than direct algorithm . aimed at measuring the large - scale network , we analyze multicast - based loss inference used multiple points and introduce minimum variance weighted average and em algorithms , and compare the difference on accuracy and 以测量大规模网络为目的,本文研究了多点多播测量技术,给出了多点多播的加权平均值算法和em算法,并比较了多点和单点在时间复杂性和估计值精度上的异同。
Workshop on generative - model based vision in conjunction with european conf . computer vision 2002 , copenhagen , denmark , june 2 , 2002 , pp . 107 - 113 . 9 bilms j . a gentle tutorial of the em algorithm and its application to parameter estimation for gaussian mixture and hidden markov models 在新提出的图模型中，充分利用了边缘纹理和形状这两种相互增强的观测信息，同时提出了一种融合形状和纹理观测信息的参数估计算法，在多姿态的人脸定位问题中取得了很好的效果。
What flow is that , we use model simulation to analyze the em algorithm contraction ratio . through network simulating , we analyze the factors which can influence loss inference algorithm accuracy like measurement strategy or routing algorithm . we analyze the accuracy and contraction characteristic of multicast - based direct algorithm and em algorithm , and compare the error factor between them 实验中通过网络仿真模型,确定了em算法的收敛速率;研究了不同测量策略和路由器拥塞避免算法对丢包率推理算法准确率的影响;分析了单点多播的de和em算法准确性、收敛性等特征,通过比较两种算法的统计误差,得出em算法略优于de算法的结论。
