搜索资源列表
-MUL_estimators-
- 本算法包括最大似然估计,最小二乘估计,基于EM算法的多种混合高斯分布估计,EM算法测试实例,绘制每种分布的plot函数。非常有参考价值! - A Collection of Fitting Functions A collection of fitting functions for various Distributions. The provided files are an excellent source for EM based Matlab work.
Gaussian-Noise-Image-Add
- 这个程序用于在图片中增加各种噪声,如高斯椒盐噪声, 加性或乘性等多种混合噪声,用于其它程序的测试。-This procedure is used to increase the variety of picture noise, such as salt and pepper Gaussian noise, additive or multiplicative noise, such as a mixture for testing other programs.
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. . .
hh
- 【 摘 要】 提出了一种基于负熵的快速不动点1 C A算法, 介绍了负熵的定义和如何将其用作代价函数度量混合信号的非 高斯性。 详细介绍了基于负熵的固定点准则以及简化算法。实验选取 3个非高斯向量作为信号源进行 Ma t l a b分离仿真, 结果显示 分离效果良好。-Abstract Based on the rapid Negentropy 1 CA fixed point algorithm, introduced the definition of negentropy an
GAUSS
- Gray先生的大作,描述高斯混合矢量量化方法进行说话人识别的方法-Daisaku Mr. Gray describes the Gaussian mixture vector quantization approach to speaker recognition method
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
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.
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
hmm
- hmm文件时运用HMM算法实现噪声环境下语音识别的。其中vad.m是端点检测程序;mfcc.m是计算MFCC参数的程序;pdf.m函数是计算给定观察向量对该高斯概率密度函数的输出概率;mixture.m是计算观察向量对于某个HMM状态的输出概率,也就是观察向量对该状态的若干高斯混合元的输出概率的线性组合;getparam.m函数是计算前向概率、后向概率、标定系数等参数;viterbi.m是实现Viterbi算法;baum.m是实现Baum-Welch算法;inithmm.m是初始化参数;trai
mixture_of_gaussians
- 一种混合高斯模型方法提取光流的matlab源程序-mixture of gaussians
GMM
- 无监督混合高斯模型(GMM)的EM估计,含两篇IEEE论文的源码-This is a set of MATLAB m-files implementing the mixture fitting algorithm described in the paper M. Figueiredo and A.K.Jain, "Unsupervised learning of finite mixture models", IEEE Transaction on Pattern Analys
guass
- matlab中可以运行的混合高斯模型,用于运动检测,提供了一个基本的程序框架,各种改进算法可以基于本程序进行-matlab can run Gaussian mixture model for motion detection, provides a basic framework of the program, various improvements to the algorithm based on the Program.
Matlab-HMM
- 基于高斯混合模型的情感识别算法 matlab -Hmm emotion recgonition
hunhegaosijianmo
- 在MATLAB环境下,用混合高斯背景建模的方法实现对视频中运动目标的检测-In the MATLAB environment, using Gaussian mixture background modeling method to achieve the detection of moving targets in the video
mixture_of_gaussians
- 混合高斯模型来进行前景背景区分的matlab实现代码-Gaussian mixture model to distinguish between foreground and background matlab implementation code
mixture_of_gaussians
- 基于混合高斯背景建模的背景差分视频目标检测方法。matlab代码-Video target detection method based on Gaussian mixture background modeling background difference. matlab code
matlab
- 根据伪随机序列理论,由混合同余法产生均匀分布的随机数,进而根据中心极限定理来产生高斯噪声。 分析所产生的均匀分布和高斯分布随机信号的均值、方差、自相关等数字特征,估计其概率密度函数并进行分析,估计其功率谱密度并进行分析。说明该高斯噪声是否符合白噪声特性。 对该高斯噪声进行FIR低通滤波,估计输出低通型限带白噪声的功率谱、相关时间等,并结合白噪声通过线性系统相关理论来进行分析。 -According to the theory of pseudo-random sequence, a
beforeground
- 在matlab平台上,基于混合高斯模型的前景提取。-Matlab platform, based on Gaussian mixture model prospects extract.