An O(log2N) Fully-Balanced Resampling Algorithm for Particle Filters on Distributed Memory Architectures

Resampling is a well-known statistical algorithm that is commonly applied in the context of Particle Filters (PFs) in order to perform state estimation for non-linear non-Gaussian dynamic models. As the models become more complex and accurate, the run-time of PF applications becomes increasingly slo...

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Bibliographic Details
Published in:	Algorithms Vol. 14; no. 12; p. 342
Main Authors:	Varsi, Alessandro, Maskell, Simon, Spirakis, Paul G.
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.12.2021
Subjects:	Accuracy Algorithms Complexity Computer architecture Distributed Memory Dynamic models high performance computing Hypotheses message passing interface parallel computing Particle Filters Resampling Run time (computers) State estimation Supercomputers Workloads
ISSN:	1999-4893, 1999-4893
Online Access:	Get full text
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