A Fast Labeled Multi-Bernoulli Filter Using Belief Propagation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU140242" target="_blank" >RIV/00216305:26220/19:PU140242 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore-ieee-org.ezproxy.lib.vutbr.cz/document/8836103" target="_blank" >https://ieeexplore-ieee-org.ezproxy.lib.vutbr.cz/document/8836103</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TAES.2019.2941104" target="_blank" >10.1109/TAES.2019.2941104</a>

Result language
angličtina
Original language name
A Fast Labeled Multi-Bernoulli Filter Using Belief Propagation
Original language description
We propose a fast labeled multi-Bernoulli (LMB) filter that uses belief propagation for probabilistic data association. The complexity of our filter scales only linearly in the numbers of Bernoulli components and measurements, while the performance is comparable to or better than that of the Gibbs sampler-based LMB filter.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20201 - Electrical and electronic engineering

Project
<a href="/en/project/GA17-19638S" target="_blank" >GA17-19638S: Sequential Bayesian Estimation of Arterial Wall Motion</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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