Approximate Likelihood for Noisy Mixtures

Abstract

This contribution addresses the problem of maximum likelihood (ML) estimation for noisy mixtures for both the square case and the overcomplete case. We consider the EM algorithm for ML estimation and derive several approximations of it in the limit of low noise and of heavy tailed source distributions. 

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