DocumentCode :
699874
Title :
A new approach to particle based smoothed marginal MAP
Author :
Saha, S. ; Mandal, P.K. ; Bagchi, A.
Author_Institution :
Dept. of Appl. Math., Univ. of Twente, Enschede, Netherlands
fYear :
2008
fDate :
25-29 Aug. 2008
Firstpage :
1
Lastpage :
5
Abstract :
We present here a new method of finding the MAP state estimator from the weighted particles representation of marginal smoother distribution. This is in contrast to the usual practice, where the particle with the highest weight is selected as the MAP, although the latter is not necessarily the most probable state estimate. The method developed here uses only particles with corresponding filtering and smoothing weights. We apply this estimator for finding the unknown initial state of a dynamical system and addressing the parameter estimation problem.
Keywords :
maximum likelihood estimation; signal processing; state estimation; MAP state estimator; marginal smoother distribution; parameter estimation problem; particle based smoothed marginal MAP; weighted particles representation; Approximation methods; Equations; Estimation; Mathematical model; Monte Carlo methods; Signal processing; Smoothing methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2008 16th European
Conference_Location :
Lausanne
ISSN :
2219-5491
Type :
conf
Filename :
7080406
Link To Document :
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