搜索资源列表
EM算法
- EM算法，用于实现高斯混合模型参数估计GMM
empca
- 用EM算法估计PCA参数，效果比传统的PCA要好，原文发表于神经计算杂志上，有兴趣者可以先看论文。-using EM algorithm parameters estimated PCA results than the traditional PCA better, in the language of neural computation published in the magazine, those who are intere
EMnormmixtest
- 经典的EM算法程序，用于正态混合分布模型的参数估计,希望能够对大家有帮助！-classic EM algorithm for the Normal Distribution hybrid model parameter estimation, we hope to be able to help!
EMalgorithmforMOG
- 高斯混合模型参数估计,EM算法,sunMOG.m为函数,testMOG4.m为测试程序-Gaussian mixture model parameter estimation, EM algorithm, sunMOG.m for the function, testMOG4.m for the test procedure
ImageFilterBasedP2DHMTModelinWaveletDomain
- 文章提出了一种基于小波域伪二维隐Markov 树（P2DHMT）的图像的滤波新方法。首先建立了小波域的伪 2DHMT 模型，给出了基于EM、Baum-Welch 等算法的模型参数估计方法；
em
- em算法是一种估计最优参数的方法 又名最大期望算法-em algorithm is a way to estimate the optimal parameters, also known as the greatest expectations algorithm
emgmm
- 本程序是EM算法，是参数估计（极大似然估计）方法的数值解法。-This procedure is the EM algorithm, is the parameter estimation (MLE) method of numerical solution.
em_ghmm
- EM算法,用于估计参数的一个初级入门实例-EM algorithm, used to estimate the parameters of a primary entry examples
em
- 混合高斯概率密度模型,其参数估计可以通过期望最大化( EM) 迭代算法获得。-EM estimation parameters Gaussian mixture processes
EM
- EM算法简明教程 用于高斯分布隐马尔可夫模型的参数估计-Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models
EM.java.tar
- EM 算法是 Dempster，Laind，Rubin 于 1977 年提出的求参数极大似然估计的一种方法，它可以从非完整数据集中对参数进行 MLE 估计，是一种非常简单实用的学习算法。这种方法可以广泛地应用于处理缺损数据，截尾数据，带有讨厌数据等所谓的不完全数据(incomplete data)。需要weka的算法包支持。-EM algorithm is Dempster, Laind, Rubin in 1977 for the p
EmEstimate
- 给定独立同分布样本集，用matlab编程实现EM算法进行参数估计-Given the independent and identically distributed sample set, using matlab programming EM algorithm to estimate parameters
ros-em
- em算法运用于有散射体的信道模型下实现参数估计（los距离）-em algorithm applied to a scattering channel model to achieve parameter estimation (los distance)
em-three-preference
- 基于EM算法，可以估计在混合高斯分布下的三个参数-EM expection
EM
- EM算法Matlab实现。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）-EM algorithm by Matlab. Maximum expected (EM) algorithm is probabilistic (probabilistic) model to find maximum likeli
EM
- 利用Matlab编程验证用EM算法估计的高斯混合模型的相关参数的性能。-Validate the use of Matlab programming estimated using EM algorithm for Gaussian mixture model parameters related to the performance.
EM
- 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 esti
EM-Algorithm
- 参数估计 EM算法 的c语言实现在linux下编译通过-Parameter estimation of EM algorithm realize the C language in the Linux under the compiler through
R
- R语言对数据进行Garch-M-Copula建模并利用EM算法估计相应的参数(Garch-m-copula is used to model the data in R language and EM algorithm is used to estimate the corresponding parameters)
EM算法用于高斯混合模型
- EM算法在高斯混合模型的参数估计中的应用，内服Matlab程序例子。(Application of Matlab program and EM algorithm in parameter estimation of Gaussian mixture model.)