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https://doi.org/10.1007/117585...
Part of book or chapter of book . 2006 . Peer-reviewed
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Quasi-Gaussian Particle Filtering

Authors: Yuanxin Wu; Dewen Hu; Meiping Wu; Xiaoping Hu 0002;

Quasi-Gaussian Particle Filtering

Abstract

The recently-raised Gaussian particle filtering (GPF) introduced the idea of Bayesian sampling into Gaussian filters. This note proposes to generalize the GPF by further relaxing the Gaussian restriction on the prior probability. Allowing the non-Gaussianity of the prior probability, the generalized GPF is provably superior to the original one. Numerical results show that better performance is obtained with considerably reduced computational burden.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
bronze