[PDF.12sl] Sequential Monte Carlo Methods for Nonlinear Discrete-Time Filtering (Synthesis Lectures on Signal Processing)

Sequential Monte Carlo Methods for Nonlinear Discrete-Time Filtering (Synthesis Lectures on Signal Processing)

[PDF.jg86] Sequential Monte Carlo Methods for Nonlinear Discrete-Time Filtering (Synthesis Lectures on Signal Processing)

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 | #3671981 in Books |  Morgan Claypool Publishers |  2013-02-11 | Original language:English | PDF # 1 |  9.25 x.23 x7.50l,.41 | File type: PDF | 100 pages

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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 approaches to static (i.e., time-...

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