9. The method of claim 1 wherein estimating the plurality of Gaussian components further comprises estimating means, covariances and mixture weights for each Gaussian component using an expectation-maximization algorithm.
9. The method of claim 1 wherein estimating the plurality of Gaussian components further comprises estimating means, covariances and mixture weights for each Gaussian component using an expectation-maximization algorithm. 10. The method of claim 9 wherein the covariances are estimated using a covariance matrix approximation wherein the covariances are diagonal matrices.