Creates an image of a Gaussian with arbitrary covariance matrix. The dimensionality and size of the filter is determined by dims (eg dims=[10 10] creates a 2D filter of size 10×10).
If C=; then C=(dims/6).^2, ie it is transformed into a vector of variances such that along each dimension the variance is equal to (siz/6)^2.
G = filterGauss( dims, [mu], [C], [show] )
dims – n element vector of dimensions of final Gaussian
mu –  n element vector specifying the mean
C –  nxn cov matrix, nx1 set of vars, or variance
show –  figure to use for optional display
G – image of the created Gaussian