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PAPEŽ, M.
Originální název
A projection-based Rao-Blackwellized particle filter to estimate parameters in conditionally conjugate state-space models
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Particle filters constitute today a well-established class of techniques for state filtering in non-linear state-space models. However, online estimation of static parameters under the same framework represents a difficult problem. The solution can be found to some extent within a category of state-space models allowing us to perform parameter estimation in an analytically tractable manner, while still considering non-linearities in data evolution equations. Nevertheless, the well-known particle path degeneracy problem complicates the computation of the statistics that are required to estimate the parameters. The present paper proposes a simple and efficient method which is experimentally shown to suffer less from this issue.
Klíčová slova
Sequential Monte Carlo; particle filtering; conditionally conjugate state-space models; Rao-Blackwellization
Autoři
Vydáno
10. 6. 2018
Nakladatel
Institute of Electrical and Electronics Engineers (IEEE)
Místo
New York
ISBN
978-1-5386-1571-3
Kniha
Proceedings of the 20th Statistical Signal Processing Workshop (SSP)
Strany od
268
Strany do
272
Strany počet
5
URL
https://www.semanticscholar.org/paper/A-Projection-Based-Rao-Blackwellized-Particle-to-in-Papez/88052a94e61c6fb9b0b27e178de9a59e707ea737
BibTex
@inproceedings{BUT148842, author="Milan {Papež}", title="A projection-based Rao-Blackwellized particle filter to estimate parameters in conditionally conjugate state-space models", booktitle="Proceedings of the 20th Statistical Signal Processing Workshop (SSP)", year="2018", pages="268--272", publisher="Institute of Electrical and Electronics Engineers (IEEE)", address="New York", doi="10.1109/SSP.2018.8450730", isbn="978-1-5386-1571-3", url="https://www.semanticscholar.org/paper/A-Projection-Based-Rao-Blackwellized-Particle-to-in-Papez/88052a94e61c6fb9b0b27e178de9a59e707ea737" }