Publisher review:EM_GM - An expectation maximization algorithm for learning a multi-dimensional Gaussian mixture. Although EM algorithm for Gaussian mixture (EM_GM) learning is well known, 3 major MATLAB EM_GM codes are found on the web. However, they either have errors or not easy to incorporate into other MATLAB codes. Therefore, I decide to write my own EM_GM and share it. My EM_GM is designed as a single file function (i.e. all sub functions are included in the same file) for convenience and portability. Detail descriptions of all inputs and outputs are included in the file. EM_GM can be controlled to plot 1D or 2D problems and display CPU time used as well as number of iterations.Example:X = zeros(600,2);X(1:200,:) = normrnd(0,1,200,2);X(201:400,:) = normrnd(0,2,200,2);X(401:600,:) = normrnd(0,3,200,2);[W,M,V,L] = EM_GM(X,3,[],[],1,[]) Requirements: · MATLAB Release: R13 · Statistics Toolbox
EM_GM is a Matlab script for Statistics and Probability scripts design by Patrick Tsui.
It runs on following operating system: Windows / Linux / Mac OS / BSD / Solaris.
EM_GM - An expectation maximization algorithm for learning a multi-dimensional Gaussian mixture.
Operating system:Windows / Linux / Mac OS / BSD / Solaris
EM_GM script details 
