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 :
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