Sequential Monte Carlo Methods for Nonlinear Discrete-Tim...
G. S., Marcelo / G. S. Bruno, Marcelo In these notes, we introduce particle filtering as a recursive importance sampling method that approximates the minimum-mean-square-error (MMSE) estimate of a sequence of hidden state vectors in scenarios where the joint probability distribution of the states and the observations is non-Gaussian and, therefore, closed-form analytical expressions for the MMSE estimate are generally unavailable.
We begin the notes with a review of Bayesian appr...