# Multivariate gaussian mixture model optimization by cross entropy in matlab

The following Matlab project contains the source code and Matlab examples used for multivariate gaussian mixture model optimization by cross entropy. Fit a multivariate gaussian mixture by a cross-entropy method.

# 1d infinite gaussian mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for 1d infinite gaussian mixture model. This is a little script which was designed for educational purposes.

# 2d infinite gaussian mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for 2d infinite gaussian mixture model. This is a little script which was designed for educational purposes.

# Gaussian mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for gaussian mixture model. Gaussian Mixture model is used in many fields to model a training set of data owing to certain similarities among them.

# Bayesian robust state space mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for bayesian robust state space mixture model. The BRSSMM class implements algorithms for simulating and estimating the parameters of a finite mixture of state-space models.

# Bayesian robust mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for bayesian robust mixture model. The BRMM class implements algorithms for simulating and estimating the parameters of a finite mixture model.

# Bayesian robust regression mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for bayesian robust regression mixture model. The BRRMM class implements algorithms for simulating and estimating the parameters of a finite mixture model.

# Em Algorithm Matlab Code

The following matlab project contains the source code and matlab examples used for em algorithm.

# Gaussian mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for gaussian mixture model. A Gaussian mixture model means that each data point is drawn (randomly) from one of C classes of data, with probability p_i of being drawn from class i, and each class is distributed as a Gaussian with mean standard deviation mu_i and sigma_i.

# Bayesian robust simplicial mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for bayesian robust simplicial mixture model. The BRSMM class implements algorithms for simulating and estimating the parameters of a finite, simplicial mixture model.

# Expectation maximization of gaussian mixture models via cuda in matlab

The following Matlab project contains the source code and Matlab examples used for expectation maximization of gaussian mixture models via cuda. This is a parallel implementation of the Expectation Maximization algorithm for multidimensional Gaussian Mixture Models, designed to run on NVidia graphics cards supporting CUDA.

# 3d visualization of gmm learning via the em algorithm in matlab

The following Matlab project contains the source code and Matlab examples used for 3d visualization of gmm learning via the em algorithm. This is a 3D visualization of how the Expectation Maximization algorithm learns a Gaussian Mixture Model for 3-dimensional data.

# Gaussian mixture model (gmm) gaussian mixture regression (gmr) in matlab

The following Matlab project contains the source code and Matlab examples used for gaussian mixture model (gmm) gaussian mixture regression (gmr). GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR).

# Expectation maximization algorithm with gaussian mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for expectation maximization algorithm with gaussian mixture model. Implementation of Expectation Maximization algorithm for Gaussian Mixture model, considering data of 20 points and modeling that data using two Gaussian distribution using EM algorithm

# Gaussian mixture modeling gui (gmm demo) in matlab

The following Matlab project contains the source code and Matlab examples used for gaussian mixture modeling gui (gmm demo). The Expectation-Maximization algorithm (EM) is widely used to find the parameters of a mixture of Gaussian probability density functions (pdfs) or briefly Gaussian components that fits the sample measurement vectors in maximum likelihood sense [1].

# Useful matlab functions for speaker recognition using adapted gaussian mixture model

The following Matlab project contains the source code and Matlab examples used for useful matlab functions for speaker recognition using adapted gaussian mixture model. Implementation details of (i)-(iii) can be found in [1].

# Gaussian mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for gaussian mixture model. The GMM returns the cluster centroid and cluster variances for a family of points if the number of clusters are predefined.

# Em algorithm for gaussian mixture model with background noise in matlab

The following Matlab project contains the source code and Matlab examples used for em algorithm for gaussian mixture model with background noise. This is the standard EM algorithm for GMMs, presented in Bishop's book "Pattern Recognition and Machine Learning", Chapter 9, with one small exception, the addition of a uniform distribution to the mixture to pick up background noise/speckle; data points which one would not want to associate with any cluster.

# Ziheng gmm in matlab

The following Matlab project contains the source code and Matlab examples used for ziheng gmm. The code implements the Gaussian mixture model. It assumes that the features are independent. Specifically, GMMtrain.m is used to learn the GMM model and GMMpredict.m is used to predict the cluster labels.

# Community detection use gaussian mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for community detection use gaussian mixture model . Overlapping community detection use Gaussian Mixture Model.Use k-means algorithm and genetic algorithm.

# Parameter estimation technique for general datasets in matlab

The following Matlab project contains the source code and Matlab examples used for parameter estimation technique for general datasets. In the paper "An estimation technique for Time Indexed gaussian Mixture Models", we propose a model specification that can be used to describe data with spikes, jumps, mean reversion, geometric brownian motion, you name it.

# Em algorithm for gaussian mixture model in matlab

The following Matlab project contains the source code and Matlab examples used for em algorithm for gaussian mixture model. This is a function tries to obtain the maximum likelihood estimation of Gaussian mixture model by expectation maximization (EM) algorithm.
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