Abstract
Probabilistic inference is the problem of estimating the hidden states of
a system in an optimal and consistent fashion given a set of noisy or incomplete
observations. The optimal solution to this problem is given by
the recursive Bayesian estimation algorithm which recursively updates
the posterior density of the system state as new observations arrive online.
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