搜索资源列表
CN_fdtd_3d_pml
- 介绍一种结合CN-FDTD方法和UPML的新算法，它能以较高的精度解决3维电磁散射问题。-this code contains a new algorithm that combines CN-FDTD and UPML which can result in low computing dispersion in solving EM problems.
machine-learning-3
- 机器学习算法之EM与K-MEANS，经典的机器学习的外文资料，该资料描述详细，便于大家的学习。-The EM machine learning algorithms with K-MEANS, classical machine learning foreign language information, the information described in detail, easy to learn from everyone.
GMM
- 通过应用matlab实现高斯算法，用EM估计GMM的数据参数，并把运算时其遗漏数据补全-Matlab achieved through the application of Gauss algorithm estimates GMM data parameters EM, and the missing data when computing its complement
KalmanAll
- 关于卡尔曼滤波的matlab代码，其中包含了滤波的主算法，以及使用EM查找最大可能的估计参数，随机样本-Kalman filter matlab code, which contains the main algorithm filtering, and the use of EM to find the best possible estimate parameters of a random sample, etc.
Clustering_Toolbox
- Robert Gordon University的一个研究人员写的k-means聚类算法工具箱，内容完整可运行。-Includes k-means, hierarchical (single-, complete- and mean-linkage), EM for Gaussian Mixture Models, fuzzy c-means, and a demo.
all-of-Cluster
- 大多数经典聚类分析算法的matlab实现，包括K均值、模糊聚类（FCM）、SOM、Kohonen、EM、DBSCAN、等！-ON划词翻译ON实时翻译 Most of the classical clustering algorithm matlab implementation, including K means, fuzzy clustering (FCM), SOM, Kohonen, EM, DBSCAN, etc.!
EM_matlab
- 是一种用于含有隐变量（hidden variable）的概率参数模型的最大似然估计或极大后验概率估计的matlab算法。 -EM MATLAB
test
- 以无约束优化问题为研究对象，基本的类电磁算法-Electromagnetism-like Mechanism，EM）
data_association
- 几种实用的包含数据关联算法的matlab代码文件，内容中包含NN,PDA,JPDA及国际上较新的EM—KF算法的仿真程序，很实用-Several practical contains matlab code file of data correlation algorithm, NN are contained in the content, PDA, JPDA and relatively new in the world is EM- KF algorithm simulation prog
ap
- 谱估计中的自回归模型（AP）算法，适合阵列信号处理初学者学习-Spectral Estimation autoregressive model (EM) algorithm
404440
- 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,()
RCY-GMMtest1
- 高斯混合模型（GMM,Gaussian Mixture Model）参数如何确立这个问题，详细讲解期望最大化（EM,Expectation Maximization）算法的实施过程。(How to establish the parameters of Gauss mixture model and explain the implementation process of the expectation maximization algorithm in detail.)