搜索资源列表
GMM
- 混合高斯em算法matlab源码可算三个参数-Em algorithm for Gaussian mixture can be considered three parameters matlab source
GMM
- 高斯模型的实现，vc 6.0环境下实现的源代码，对于初学者有很好的借鉴作用-The realization of Gaussian model, vc 6.0 environment to achieve the source code, for the beginners have a good reference
GMM-GMR-v1.2
- 这是一款用matlab编写的GMM算法，有样例，实现用EM算法寻找GMM参数-This is a matlab prepared using GMM algorithm, there is a sample, look for implementation using EM algorithm for GMM parameter
GMM
- 利用K-高斯混合模型提取视频的前景信息。-The use of K-Gaussian mixture model for the future of video information extraction
08gmm
- GMM很好的理论资料,对高斯模型的详细描述以及EM算法的介绍。对编程有一定的帮助。-This is for the initial researcher to study about the GMM Model.
backmodel
- EM-GMM建立背景模型，用于运动物体检测，侵入检测等-EM-GMM background model set up for moving object detection, intrusion detection, etc.
em
- Expectation Maximization for training GMM s, diagonal covariances. Requires vqtrain.m to have a good initialization.
gmm
- 求高斯混合模型的EM算法，matlab程序。-Seeking EM algorithm for Gaussian mixture model, matlab program.
EM-GMM
- Em algo for GMM, data mining unsupervised learning-Em algo for GMM, data mining unsupervised learning
em-algorithm-for-gmm
- 基于高斯混合模型(GMM)的em算法，给出了其matlab实现-em algorithm for GMM
emgm
- em for n-dimensional g-em for n-dimensional gmm
em
- EM算法的Matlab实现，针对GMM模型-EM algorithm for GMM Model
GMM_EM
- 2类分类高斯混合模型 使用k-means的方法来初始化GMM， 基于EM算法计算出GMM模型参量。 测试GMM模型分别有2个，4个，8个混合成分-2-class classifier with Gaussian Mixture Models. Use the k-means method to initialize the GMM’s Then improve the GMM models iteratively based on the EM algo-rithm.
GMM
- 程序展示了使用EM algorithm来训练GMM(Gaussian Mixture Model)来进行binary classification。-Program demonstrates the use of EM algorithm to train the GMM (Gaussian Mixture Model) for binary classification.
EM-Algorithm-for-GMM
- Expectation Maximization algorithm for Gaussian Mixture Model Training
EmGMM
- 高斯混合模型的最大期望迭代求解算法,可用于图像区域灰度分布估计-Expectation maximazation(EM) for Gaussian mixture model(GMM)
emgmm
- em algorithm for g-em algorithm for gmm
EM_GMM-master
- em-gmm-master good for gmm algorithm
em
- em算法介绍:EM算法有很多的应用，最广泛的就是GMM混合高斯模型、聚类、HMM等等(This is the EM algorithm using JAVA, easy to understand, easy to use and helpful for understanding the EM algorithm)
GMM_EM
- GMM算法是混合高斯模型，其求解过程需要不断迭代，本程序利用EM算法进行了仿真实现，可以加深对GMM的理解。(GMM algorithm is a hybrid Gauss model, and its solution process needs iteration. This program uses EM algorithm for simulation, which can deepen the understanding of GMM.)