搜索资源列表
EM
- EM algorithm for adaptive multivariate Gaussian mixtures
lect26-em
- EM algorithm for adaptive multivariate Gaussian mixtures
OS-EM.ps
- another NDFT algorithm for signal processing
EMAlgorithm
- EM算法的详细介绍（含PDF文件）及其matlab实现-EM algorithm is a detailed descr iption (including PDF files) and its implementation matlab
demoEM1
- implementation of em algorithm
Bayes_EM
- 利用matlab实现的基于EM算法的贝叶斯分类器的源代码，可以用来分类或识别，很值得收藏-Using matlab to achieve EM algorithm based on Bayesian classifier of the source code can be used to classification or identification, it is worthy of collection
EMAlgorithm
- 上数据挖掘课的课件，是EM算法的，其中还包括最大似然值，最大似然估计，以及cluster-data mining,EM Algorithm ,Likelihood, Mixture Models and Clustering
emforgaussian
- em algorithm for gaussion -em for gaussion
EM_1D
- 一维EM算法MATLAB实现，两分支高斯混合模型，均值和方差都不相同。-one dimensino EM algorithm implemented by MATLAB. Estimate the mean and variance of Gaussian Mixture Model with two branches.
EM
- the EM algorithm and extensions.pdf
gmm
- 求高斯混合模型的EM算法，matlab程序。-Seeking EM algorithm for Gaussian mixture model, matlab program.
EMsuanfa
- EM算法，好好学，图像处理，图像分割，一定能成功-EM algorithm, good science, image processing, image segmentation, will succeed
ythirr
- EM algorithm mean shift algorithm for image segmentation, at the same time have demo program with the ultimate view of segmentation results
MLDemos-0.1.2-win
- gaussian mixture and em algorithm
demo1
- 我自己写的关于二维混合高斯分布的EM算法-I wrote about the distribution of two-dimensional Gaussian mixture EM algorithm
freqBlind-Em
- 文章根据频率选择性衰落信道的抽头延迟线模型，将针对平坦衰落信道的CS(周期平稳过程理论)频偏盲估计 算法扩展到了频率选择性衰落信道，并通过仿真证明这种扩展是可行的.仿真结果还表明CS算法不仅有好的抗平 坦衰落能力，而且有很好的杭频率选择性衰落性能.-Article according to frequency selective fading channel tap delay line model, the flat fading channel for CS (cycle stati
EMgaussian
- EM算法求高斯过程的参数,这种算法的计算过程简单，但是准确度不高-EM algorithm for getting the parameters of Gaussian process, this computation is simple, but accuracy is not high
EMALGORITHM
- 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
emgmgm
- EM algorithm for Gaussian mixture
EM_Algorithm
- EM algorithm is to solute the problem of parameter maximum likelihood estimation by Dempster, Laind, Rubin in 1977. The EM algorithm can estimate maximum likelihood only through incomplete data set. -EM algorithm is to solute the problem of parame