On Sequential Simulation-Based Methods for Bayesian Filtering

@techreport{Doucet1998, abstract = {. In this report, we present an overview of sequential simulationbased methods for Bayesian filtering of nonlinear and non-Gaussian dynamic models. It includes in a general framework numerous methods proposed independently in various areas of science and proposes some original developments. Keywords: Bayesian estimation, optimal filtering, nonlinear non-Gaussian state space models, hidden Markov models, sequential Monte Carlo methods. 1. Introduction 1 Many problems in statistical signal...}, author = {Doucet, Arnaud }, citeulike-article-id = {347943}, institution = {Cambridge University Department of Engineering}, keywords = {bayesian, ee520, ee520\_part1, filtering, monte-carlo}, number = {CUED/F-INFENG/TR. 310}, posted-at = {2005-10-11 17:00:19}, priority = {2}, title = {On Sequential Simulation-Based Methods for Bayesian Filtering}, url = {http://citeseer.ist.psu.edu/doucet98sequential.html}, year = {1998} }

TY - RPRT ID - Doucet1998 L3 - citeulike-article-id:347943 TI - On Sequential Simulation-Based Methods for Bayesian Filtering IS - CUED/F-INFENG/TR. 310 N2 - . In this report, we present an overview of sequential simulationbased methods for Bayesian filtering of nonlinear and non-Gaussian dynamic models. It includes in a general framework numerous methods proposed independently in various areas of science and proposes some original developments. Keywords: Bayesian estimation, optimal filtering, nonlinear non-Gaussian state space models, hidden Markov models, sequential Monte Carlo methods. 1. Introduction 1 Many problems in statistical signal... KW - bayesian KW - ee520 KW - ee520_part1 KW - filtering KW - monte-carlo AU - Doucet, Arnaud PY - 1998/// UR - http://citeseer.ist.psu.edu/doucet98sequential.html ER -