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用matlab语言写的EM(Expectation maximization)算法,用于模式分类
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EM算法介绍及Matlab演示代码(一维和多维高斯混合模型学习算法)-Introduction of EM algorithm and Matlab codes that implement the algorithm
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用于估计未知数据的EM算法，即最大期望算法，用到的地方很多，可用来做同步。-The data used to estimate the unknown EM algorithm, that is the maximum expectation algorithm, used in many places, can be used for synchronization.
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duke的tutorial on EM的matlab经典源码，值得一看。-Matlab code for the tutorial on Expectation Maximization，worth a visit.
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基于em算法的图象分割程序,是图象分割的一类重要算法.-Em algorithm based on image segmentation process of image segmentation are essential for a class of algorithms.
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2008年3月
中国图象图形学报
基于类自适应高斯-马尔可夫随机场模型和EM 算法的MR图像分割
比较新的一片关于MARKOV以及EM算法的图像分割的文章。详细介绍了两种算法，以及对MR图像的实验结果，很有参考价值-March 2008 Journal of Image and Graphics of China based on the type of adaptive Gaussian- Markov random field model and the EM algorithm
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This package contains Matlab m-files for learning finite Gaussian mixtures from sample data and performing data classification with Mahalanobis distance or Bayesian classifiers. Each class in training set is learned individually with one of the three
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Expectation-maximization algorithm
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Expectation Maximization for training GMM s, diagonal covariances. Requires vqtrain.m to have a good initialization.
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GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR). It allows to encode efficiently any dataset in Gaussian Mixture Model (GMM) through the use of an Ex
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GUI for an Expectation-Maximization algorithm (EM) variant (Split-EM-Discriminant)
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采用EM，期望最大方法，估计QPSK调制方式下的信噪比-Using EM, expectation maximization method to estimate the signal to noise ratio under QPSK modulation
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In statistics, an expectation-maximization (EM) algorithm is a method for finding maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. EM is an iterati
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EM算法 , EM算法是机器学习中一个很重要的算法，即期望最大化算法-EM algorithm, EM algorithm is a very important machine learning algorithm, that is, expectation maximization algorithm
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求解参数估计的常用算法——EM，即期望最大化算法，用于代替样本量不完全时的极大似然估计算法。-Common algorithm for solving parameter estimation- EM, expectation maximization algorithm is used to replace the sample size is not completely at the maximum likelihood estimation algorithm.
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Expectation-Maximization algorithm
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Expectation-Maximization algorithm for a HMM with Multivariate Gaussian measurement
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[logl , PI , A , M , S] = em_ghmm(Z , PI0 , A0 , M0 , S0 , [options])
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自己小结的期望最大化算法（EM算法），很详细。-Own summary of the expectation-maximization algorithm (EM algorithm), in great detail.
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自己编写的期望最大化（EM）算法的MATLAB实现，里面有较为运行方法和程序说明，对新手有很好的帮助-
I have written the expectation-maximization (EM) algorithm in MATLAB, which has run more methods and procedures described, there is a good help for the novice
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在统计计算中，最大期望（EM）算法是在概率（probabilistic）模型中寻找参数最大似然估计或者最大后验估计的算法，其中概率模型依赖于无法观测的隐藏变量（Latent Variable）。最大期望经常用在机器学习和计算机视觉的数据聚类（Data Clustering）领域。(In statistical calculation, the expectation maximization (EM) algorithm in probability (probabilistic) maximu
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