搜索资源列表
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 interested can read papers.
EM算法
- EM算法，用于实现高斯混合模型参数估计GMM
EM.zip
- 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
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
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 likelihood parameter estimation or m
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
- 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
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
- 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 estimation algorithm.
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
em(1)
- EM算法实现高斯混合模型参数估计的matlab程序，可以下载学习。-EM algorithm to achieve the matlab program Gaussian mixture model parameter estimation, you can download the study.
EM-suanfa-hunhegaosi
- em算法计算混合高斯模型的参数估计，极大似然，EM算法用于K均值问题的参数估计。MATLAB实现有代码-em algorithm Gaussian mixture model parameter estimation, maximum likelihood parameter estimation for K-means problem EM algorithm. MATLAB implementation code
EM-algorithm
- 主要介绍了EM算法（最大期望算法），该方法用于参数估计，相较于MLE算法更为简单。-em algorithm
EM算法
- 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
em
- 在统计计算中，最大期望（EM）算法是在概率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性变量。最大期望算法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 computation, the maximum expectation (EM) algorithm is an algorithm to find the maximum likelihood estimation or the maximum
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.)