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generic particle filter estimates the posterior distribution of the hidden states using the observation measurement process. With respect to a state-space such as the one below:

: the filtering problem is to estimate sequentially the values of the hidden states , given the values of the observation process at any time step k.

All Bayesian estimates of follow from the posterior density . The particle filter methodology provides an approximation of these conditional probabilities

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