GMM projects and source code

Gmm Matlab Code

Generalized method of moments (GMM) is a generic method for estimating parameters in statistical models. Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the distribution function of the data may not be known, and therefore the maximum likelihood estimation is not applicable.

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.

Gmm hmrf in matlab

The following Matlab project contains the source code and Matlab examples used for gmm hmrf. In this project, we first study the Gaussian-based hidden Markov random field (HMRF) model and its expectation-maximization (EM) algorithm.
Subscribe to RSS - GMM