Fast EM_GM

An expectation maximization algorithm for learning a multi-dimensional Gaussian mixture.

EM_GM_fast is the modified version of EM_GM (EM algorithm for k multidimensional Gaussian mixture estimation) for speed enchancement suggested by Mr. Michael Boedigheimer. The functionalities of EM_GM_fast and EM_GM are identical.
Note: EM_GM_fast requires more memory than EM_GM to execute. If EM_GM_fast does not provide any speed gain or is slower than EM_GM, more memory is needed or EM_GM should be used instead.

Similar to EM_GM, EM_GM_fast 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_fast 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_fast(X,3,[],[],1,[])