wolffd@0: wolffd@0: wolffd@0: wolffd@0: Netlab Reference Manual demgmm1 wolffd@0: wolffd@0: wolffd@0: wolffd@0:

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wolffd@0: Purpose wolffd@0:

wolffd@0: Demonstrate density modelling with a Gaussian mixture model. wolffd@0: wolffd@0:

wolffd@0: Synopsis wolffd@0:

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wolffd@0: demgmm1

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wolffd@0: Description wolffd@0:

wolffd@0: The problem consists of modelling data generated by a mixture of three wolffd@0: Gaussians in 2 dimensions. The priors are 0.3, wolffd@0: 0.5 and 0.2; the centres are (2, 3.5), (0, 0) and (0,2); the variances wolffd@0: are 0.2, 0.5 and 1.0. The first figure contains a wolffd@0: scatter plot of the data. wolffd@0: wolffd@0:

A Gaussian mixture model with three components is trained using EM. The wolffd@0: parameter vector is printed before training and after training. The user wolffd@0: should press any key to continue at these points. The parameter vector wolffd@0: consists of priors (the column), centres (given as (x, y) pairs as wolffd@0: the next two columns), and variances (the last column). wolffd@0: wolffd@0:

The second figure is a 3 dimensional view of the density function, while wolffd@0: the third shows the 1-standard deviation circles for the three components of wolffd@0: the mixture model. wolffd@0: wolffd@0:

wolffd@0: See Also wolffd@0:

wolffd@0: gmm, gmminit, gmmem, gmmprob, gmmunpak

wolffd@0: Pages: wolffd@0: Index wolffd@0:

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