搜索资源列表
gmm_test.rar
- 使用EM算法模拟高斯混合模型（GMM）的构成,Analog EM algorithm using Gaussian mixture model (GMM) the composition of
GMM.zip
- Gaussian Mixture Model Simulation Source,Gaussian Mixture Model Simulation Source
GMM
- 混合高斯模型的C++程序，封装成为C++的类，直接调用即可。-gaussian mixture model train code
GMM-modeling-and-EM
- 介绍Opencv这个图像处理库环境下的GMM建模与EM算法，从数学的角度深入分析高斯建模和EM算法-Introduce the the Opencv this image processing GMM modeling the EM algorithm in the library environment, in-depth analysis from a mathematical point of the Gaussian model and the EM algorithm
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
05-a
- 本文章描述了说话人识别中GMM模型中的聚类算法的研究-This article describes the GMM Speaker Recognition Model Clustering Algorithm
a_novel_speake_identification_system_based_on_GMM_
- 文中详细介绍了一种基于GMM 与 SVM的说话人识别系统。包括特征提取，算法实现及实验数据。对语音处理及说话人识别技术的研究者很有帮助。-Introduce a novel speake identification system based on GMM and SVM,with feature extract,algorithm research and experiment data.This doc would be helpful to those who are working on
Kjunzhijulei
- 用于说话人识别初始化样本的聚类算法 调试成功-Speaker Recognition for initialization of the clustering algorithm samples
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.
GMM_Purdue
- 基于混合高斯模型（GMM）的无监督聚类算法，希望对大家有帮助-Based on Gaussian mixture model (GMM) unsupervised clustering algorithm, I hope it would have help to you！
paper_ICIP06
- 视频流中前景背景分离非常不错的算法。能适应阴影，水波，树枝晃动等复杂环境-BACKGROUND MODELING FROM GMM LIKELIHOOD COMBINED WITH SPATIAL AND COLOR COHERENCY
GaussianMixtureModels
- GMM Model Gaussian Mixture Models - Algorithm and Matlab Code-GMM Model!
TutorialonGMM-Kmean-VitebeAlgorithms
- GMM和KMean算法的易懂教程及Matlab实现、Vitebe译码算法的Matlab实现-Tutorial on GMM and KMean and Vitebe algorithms and their implementation in Matlab
GMM_background_src
- 基于有限混合高斯模型的数据分类 1、使用基于有限高斯混合模型的EM算法对数据样本进行归类 2、使用C++或者Matlab语言编程环境实现该算法，并用给定的数据包对算法的正确性进行检验 -Gaussian mixture model based on limited data classification 1, using the finite Gaussian mixture model based on EM algorithm to classify the data sam
GMM-GMR-v2.0
- 基于泛化自回归的源模型，以及在这个模型基础上的EM算法实现-Generalization based on the source from the regression model, as well as in the model based on EM algorithm
em
- 基于EM算法的模型聚类的研究及应用，GMM高斯混合模型-EM-based clustering algorithm and its application model, GMM Gaussian mixture model
speakerrecognition
- 本程序是基于matlab的语者识别系统。采用mfcc算法进行提取语音特征，用gmm算法进行匹配。-This procedure is based on a speaker recognition system matlab. Mfcc algorithm using speech feature extraction, matching algorithms using gmm.
Density_Estimation
- 分别采用GMM和KDE对Iris数据集进行密度建模，并进行对比。通过EM算法来确定GMM参数，通过交叉验证来确定K值-GMM and KDE respectively Iris data set of density modeling, and compared. GMM by EM algorithm to determine the parameters of K determined by the value of cross-validation
js_gmm_Lee
- 根据Lee与2005年发表的混合高斯模型背景建模的论文编写的源代码，可以作为对GMM算法改进的一个参考。-According to Lee s paper published in 2005 about GMM background modeling, it is written in C. It should be a reference for those who are intrested in GMM algorithm improvement.
gmm
- 混合高斯算法实现及一些自己对高斯混合模型的理解。-Gaussian mixture algorithm and some experience