Abstract
A promising method for solving statistical problems in image analysis and integral equations is to add a smoothing step after the usual expectation and maximization steps of the EM algorithm (Silverman, 1990). This article gives some connections between this algorithm, known as EMS, and maximizing a penalized likelihood and derives an upper bound on the convergence rate.
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