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Software Analysis Unifying Particle Filtering and Marginalized Particle Filtering
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SYSNO ASEP 0347219 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Software Analysis Unifying Particle Filtering and Marginalized Particle Filtering Author(s) Šmídl, Václav (UTIA-B) RID, ORCID Source Title Proceedings of the 13th International Conference on Information Fusion. - Edinburgh : IET, 2010 - ISBN 978-0-9824438-1-1 Pages s. 1-7 Number of pages 7 s. Publication form www - www Action 13th International Conference on Information Fusion Event date 26.07.2010-29.07.2010 VEvent location Edinburgh Country GB - United Kingdom Event type WRD Language eng - English Country GB - United Kingdom Keywords marginalized particle filter ; software analysis ; Bayesian filtering Subject RIV BC - Control Systems Theory R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) GP102/08/P250 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation Abstract Particle filtering has evolved into wide range of techniques giving rise to many implementations and specialized algorithms. In theory, all these techniques are closely related, however this fact is usually ignored in software implementations. In this paper, particle filtering is studied together with marginalized particle filtering and a generic software scheme unifying these two areas is proposed. It is presented in general terms of object-oriented programming so that it may be implemented in existing Bayesian filtering toolboxes that are briefly reviewed. The power of the approach is illustrated on a new variant of the marginalized particle filter. A range of new variants of the filter is obtained by plugging this class into the proposed software structure. The framework and the illustrative example is implemented in the BDM library. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2011
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