Hi,
I understand you want to generate a Gaussian mixture distribution consisting of 3 overlapping single Gaussian distributions. This can be done by generating 3 Gaussian distributions with different means lying close enough so that they overlap, and using the "gmdistribution" function. The "gmdistribution" function has the following signature:
m = gmdistribution(mu,sigma,p)
This creates a Gaussian mixture model object "m" using the specified means "mu" and covariances "sigma" of the individual models with mixing proportions "p".
You can read more about the "gmdistribution" function here:
I hope this helps!
