DocumentCode
29561
Title
Modal Trajectory Estimation Using Maximum Gaussian Mixture
Author
Monin, A.
Author_Institution
LAAS, Toulouse, France
Volume
58
Issue
3
fYear
2013
fDate
Mar-13
Firstpage
763
Lastpage
768
Abstract
This technical note deals with the estimation of the whole trajectory of a stochastic dynamic system with highest probability, conditionally upon the past observation process, using a maximum Gaussian mixture. We first recall the Gaussian sum technique applied to minimum variance filtering. It is then shown that the same concept of Gaussian mixture can be applied in that context, provided we replace the Sum operator by the Max operator.
Keywords
Gaussian processes; estimation theory; filtering theory; mathematical operators; stochastic processes; Gaussian sum technique; Max operator; Sum operator; maximum Gaussian mixture; minimum variance filltering; modal trajectory estimation; past observation process; stochastic dynamic system whole trajectory; Approximation algorithms; Approximation methods; Bayesian methods; Kalman filters; Noise; Probability density function; Trajectory; Filtering; Gaussian mixture; Gaussian sum; smoothing;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.2012.2211439
Filename
6257427
Link To Document