@inproceedings{a262a7b5b04e47d69add57e33e3aed1d,
title = "Feedback particle filter with mean-field coupling",
abstract = "A new formulation of the particle filter for nonlinear filtering is presented, based on concepts from optimal control, and from the mean-field game theory. The optimal control is chosen so that the posterior distribution of a particle matches as closely as possible the posterior distribution of the true state given the observations: This is achieved by introducing a cost function, defined by the Kullback-Leibler (K-L) divergence between the actual posterior, and the posterior of any particle.",
author = "Tao Yang and Mehta, {Prashant G.} and Meyn, {Sean P.}",
year = "2011",
doi = "10.1109/CDC.2011.6160950",
language = "English (US)",
isbn = "9781612848006",
series = "Proceedings of the IEEE Conference on Decision and Control",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7909--7916",
booktitle = "2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011",
address = "United States",
note = "2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 ; Conference date: 12-12-2011 Through 15-12-2011",
}