Abstract
Two-filler formulae for the Bayes solution of the fixed-interval discrete-time nonlinear smoothing problem are obtained. The smoothed a posteriori density is computed under the assumptions of a general Markov signal observed through a general memoryless noisy channel. The case where there is feedback from the observation to the signal is also considered. The derived algorithms complement a two-pass algorithm obtained under somewhat more restrictive assumptions by Askar and Derin (1981). Known smoothing results for the linear gaussian case are interpreted in the light of the general bayesian results
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