An efficient multiple particle filter based on the variational Bayesian approach

Handle URI:
http://hdl.handle.net/10754/595410
Title:
An efficient multiple particle filter based on the variational Bayesian approach
Authors:
Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim ( 0000-0002-3751-4393 )
Abstract:
This paper addresses the filtering problem in large-dimensional systems, in which conventional particle filters (PFs) remain computationally prohibitive owing to the large number of particles needed to obtain reasonable performances. To overcome this drawback, a class of multiple particle filters (MPFs) has been recently introduced in which the state-space is split into low-dimensional subspaces, and then a separate PF is applied to each subspace. In this paper, we adopt the variational Bayesian (VB) approach to propose a new MPF, the VBMPF. The proposed filter is computationally more efficient since the propagation of each particle requires generating one (new) particle only, while in the standard MPFs a set of (children) particles needs to be generated. In a numerical test, the proposed VBMPF behaves better than the PF and MPF.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)
Conference/Event name:
2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)
Issue Date:
7-Dec-2015
DOI:
10.1109/ISSPIT.2015.7394338
Type:
Conference Paper
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7394338
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAit-El-Fquih, Boujemaaen
dc.contributor.authorHoteit, Ibrahimen
dc.date.accessioned2016-02-02T14:00:29Zen
dc.date.available2016-02-02T14:00:29Zen
dc.date.issued2015-12-07en
dc.identifier.doi10.1109/ISSPIT.2015.7394338en
dc.identifier.urihttp://hdl.handle.net/10754/595410en
dc.description.abstractThis paper addresses the filtering problem in large-dimensional systems, in which conventional particle filters (PFs) remain computationally prohibitive owing to the large number of particles needed to obtain reasonable performances. To overcome this drawback, a class of multiple particle filters (MPFs) has been recently introduced in which the state-space is split into low-dimensional subspaces, and then a separate PF is applied to each subspace. In this paper, we adopt the variational Bayesian (VB) approach to propose a new MPF, the VBMPF. The proposed filter is computationally more efficient since the propagation of each particle requires generating one (new) particle only, while in the standard MPFs a set of (children) particles needs to be generated. In a numerical test, the proposed VBMPF behaves better than the PF and MPF.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7394338en
dc.titleAn efficient multiple particle filter based on the variational Bayesian approachen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)en
dc.conference.date7-10 Dec. 2015en
dc.conference.name2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)en
dc.conference.locationAbu Dhabi, United Arab Emiratesen
dc.eprint.versionPublisher's Version/PDFen
kaust.authorAit-El-Fquih, Boujemaaen
kaust.authorHoteit, Ibrahimen
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