A survey of convergence results on particle filtering for practitioners

@misc{citeulike:2680180, abstract = {Optimal filtering problems are ubiquitous in signal processing and related fields. Except for a restricted class of models, the optimal filter does not admit a closed-form expression. Particle filtering methods are a set of flexible and powerful sequential Monte Carlo methods designed to solve the optimal filtering problem numerically. The posterior distribution of the state is approximated by a large set of Dirac-delta masses (samples/particles) that evolve randomly in time according to the...}, author = {Crisan, D. and Doucet, A. }, citeulike-article-id = {2680180}, keywords = {filter, particle}, posted-at = {2008-04-17 06:48:36}, priority = {2}, title = {A survey of convergence results on particle filtering for practitioners}, url = {http://citeseer.ist.psu.edu/crisan02survey.html}, year = {2002} }

TY - GEN ID - citeulike:2680180 L3 - citeulike-article-id:2680180 TI - A survey of convergence results on particle filtering for practitioners N2 - Optimal filtering problems are ubiquitous in signal processing and related fields. Except for a restricted class of models, the optimal filter does not admit a closed-form expression. Particle filtering methods are a set of flexible and powerful sequential Monte Carlo methods designed to solve the optimal filtering problem numerically. The posterior distribution of the state is approximated by a large set of Dirac-delta masses (samples/particles) that evolve randomly in time according to the... KW - filter KW - particle AU - Crisan, D AU - Doucet, A PY - 2002/// UR - http://citeseer.ist.psu.edu/crisan02survey.html ER -