搜索资源列表
Cross-Entropy
- 交叉熵实现多元高斯混合模型优化的源代码，供大家学习使用-Realize cross-entropy optimization of multi-Gaussian mixture model of the source code for the U.S. study the use of
markov
- 基于高斯混合模型markov树算法的图像分割-Gaussian mixture model based markov tree algorithm for image segmentation. . .
GMM
- :高斯混合模型(GMM)是一种经典的说话人识别算法，本文在实现其算法的同时，主要模拟了不同噪声环境情况下高斯混合模型 (GMM)的杭嗓声性能，得到了一些有益结论。 -Gaussian mixture model (GMM) is a classic speaker recognition algorithms, this algorithm at the same time in fulfilling its main simulated environmental conditions
11912869gmm-gmr
- 高斯混合模型，为了减少语者自己语音本身的变异性，只留下语者间彼此的变异性，在建立语者特定模型时，先训练一个语者不特定模型，-interpriter
gmmMatlab
- 关于高斯混合模型（GMM）的matlab源代码-是用于训练分类的不错的源代码-On the Gaussian mixture model (GMM) of the matlab source code- is used to train a good classification of the source code
matlab_utilities
- 粒子滤波、无迹粒子滤波算法程序，高斯混合模型参数设置等详细代码-Particle filter, unscented particle filter program, Gaussian mixture model parameter settings, and more code
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.
NSCTtransform
- 基于高斯混合模型的NSCT变换遥感图像融合-Gaussian Mixed Model Based NSCT Remote Sensing Image Fusion
VBEMGMM
- 用Matlab写的高斯混合模型的贝叶斯EM估计，-Variational Bayesian EM for Gaussian mixture models
GMMspeakers
- 用高斯混合模型来实现说话人识别的源代码，识别效果挺好的-Using Gaussian mixture model to achieve the source code for speaker recognition, recognition results in very good shape
modelbasedonspectrumprediction
- 文章展示了基于高斯混合模型的语音频谱预测方法。频谱预测可能在传包过程中预防丢包这方面起到大作用。期望最大化算法用两倍或三倍的连续语音因素来测试模型。模型被用来设计第一，儿等指令预测量。预测表用频谱分配状态来估计并和一个简单的参考模型对比。最好的预测表得到一个平均频率扭曲值是0.46dB小于参考模型-This paper presents methods for speech spectrum prediction based on Gaussian mixture models. Spec
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
GMMandSGM
- 一篇详细的介绍高斯混合模型（GMM）参数优化及实现的文档，有实例, 包括VC及matlab 实现。初始学者一看就能懂-A detailed descr iption of Gaussian mixture model (GMM) parameter optimization, and implementation documentation, including the VC and the matlab implementation
GMM-Libraries-for-Matlab
- GMM-GMR!高斯混合模型-高斯混合回归-Gaussian Mixture model-Gaussian Mixture Regression!
mixture_of_gaussians
- 这个程序是基于混合高斯背景模型的运动目标检测算法，m文件和所用视频放到matlab的工作目录下即可运行-This program is based on the Gaussian mixture background model of moving target detection algorithm, m, and used video files into matlab working directory to run
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.
交叉熵优化高斯混合模型
- matlab最大似然优化与交叉熵(CE)多高斯混合估计算法的应用(Maximum Likelihood Optimization and Cross Entropy (CE) Multi - Gaussian Mixture Estimation Algorithm)
mixture_of_gaussians
- 采用高斯混合模型来对目标进行前景检测，并用MATLAB实现。(The Gauss mixture model is used to detect the foreground of the target, and it is implemented by MATLAB.)
基于高斯混合模型（GMM）的说话人识别matlab
- 基于GMM的话者识别matlab程序，训练运行train.m,识别运行recog.m(speaker identification system based on GMM)
3-基于高斯混合模型的语音识别
- 基于高斯混合模型的语音识别，有完整的数据集和matlab代码(Speech recognition based on Gaussian mixture model, complete data set and matlab code)