A projection-based Rao-Blackwellized particle filter to estimate parameters in conditionally conjugate state-space models

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

A projection-based Rao-Blackwellized particle filter to estimate parameters in conditionally conjugate state-space models

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

A projection-based Rao-Blackwellized particle filter to estimate parameters in conditionally conjugate state-space models

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 20th Statistical Signal Processing Workshop (SSP)

ISBN

978-1-5386-1571-3

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

268-272

Název nakladatele

Institute of Electrical and Electronics Engineers (IEEE)

Místo vydání

New York

Místo konání akce

Freiburg im Breisgau

Datum konání akce

10. 6. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000720116000055