A projection-based Rao-Blackwellized particle filter to estimate parameters in conditionally conjugate state-space models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU128433" target="_blank" >RIV/00216305:26220/18:PU128433 - isvavai.cz</a>
Result on the web
<a href="https://www.semanticscholar.org/paper/A-Projection-Based-Rao-Blackwellized-Particle-to-in-Papez/88052a94e61c6fb9b0b27e178de9a59e707ea737" target="_blank" >https://www.semanticscholar.org/paper/A-Projection-Based-Rao-Blackwellized-Particle-to-in-Papez/88052a94e61c6fb9b0b27e178de9a59e707ea737</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SSP.2018.8450730" target="_blank" >10.1109/SSP.2018.8450730</a>
Alternative languages
Result language
angličtina
Original language name
A projection-based Rao-Blackwellized particle filter to estimate parameters in conditionally conjugate state-space models
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 20th Statistical Signal Processing Workshop (SSP)
ISBN
978-1-5386-1571-3
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
268-272
Publisher name
Institute of Electrical and Electronics Engineers (IEEE)
Place of publication
New York
Event location
Freiburg im Breisgau
Event date
Jun 10, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000720116000055