The AECM algorithm achieves faster stable convergence than SAGE for deterministic maximum likelihood direction-of-arrival estimation in Gaussian mixture noise while maintaining similar per-iteration computational complexity.
The EM algorithm— an old folk-song sung to a fast new tune
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The AECM Algorithm for Deterministic Maximum Likelihood Direction Finding in the Presence of Gaussian Mixture Noise
The AECM algorithm achieves faster stable convergence than SAGE for deterministic maximum likelihood direction-of-arrival estimation in Gaussian mixture noise while maintaining similar per-iteration computational complexity.