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Entropy based adaptive particle filter CLASSICAL, UNSCENTED AND PARTICLE FILTERING METHODS
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Liverani, Silvia and Papavasiliou, Anastasia (2006) Entropy based adaptive particle filter CLASSICAL, UNSCENTED AND PARTICLE FILTERING METHODS. In: IEEE Nonlinear Statistical Signal Processing Workshop, Corpus Christi Coll, Cambridge, ENGLAND, SEP 13-15, 2006. Published in: NSSPW: NONLINEAR STATISTICAL SIGNAL PROCESSING WORKSHOP pp. 87-90. ISBN 978-1-4244-0579-4.
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Abstract
We propose a particle filter for the estimation of a partially observed Markov chain that has a non dynamic component. Such systems arise when we include unknown parameters or when we decompose non ergodic systems to their ergodic classes. Our main assumption is that the value of the non dynamic component determines the limiting distribution of the observation process. In such cases, we do not want to resample the particles that correspond to the non dynamic component of the Markov chain. Instead, we take a weighted average of particle filters corresponding to different values of the non dynamic component. The computation of the weights is based on entropy and the number of particles corresponding to each particle filter is proportional to the weights.
Item Type: | Conference Item (UNSPECIFIED) | ||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||
Journal or Publication Title: | NSSPW: NONLINEAR STATISTICAL SIGNAL PROCESSING WORKSHOP | ||||
Publisher: | IEEE | ||||
ISBN: | 978-1-4244-0579-4 | ||||
Official Date: | 2006 | ||||
Dates: |
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Number of Pages: | 4 | ||||
Page Range: | pp. 87-90 | ||||
Publication Status: | Published | ||||
Title of Event: | IEEE Nonlinear Statistical Signal Processing Workshop | ||||
Location of Event: | Corpus Christi Coll, Cambridge, ENGLAND | ||||
Date(s) of Event: | SEP 13-15, 2006 |
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