On Nonlinearity Measuring Aspects of Stochastic Integration Filter

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F16%3A43929120" target="_blank" >RIV/49777513:23520/16:43929120 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5220/0005983903530361" target="_blank" >http://dx.doi.org/10.5220/0005983903530361</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0005983903530361" target="_blank" >10.5220/0005983903530361</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On Nonlinearity Measuring Aspects of Stochastic Integration Filter

Popis výsledku v původním jazyce

The paper deals with Bayesian state estimation of nonlinear stochastic dynamic systems. The focus is aimed at the stochastic integration filter, which is based on a stochastic integration rule. It is shown that the covariance matrix of the integration error calculated as a byproduct of the rule can be used as a measure of nonlinearity. The measure informs the user about validity of the assumptions of Gaussianity, which is adopted by the stochastic integration filter. It is also demonstrated how to use this information for a prediction of the number of remaining iterations of the rule. The paper also focuses on utilization of the integration error covariance matrix for improving estimates of the mean square error of the estimates, which is produced by the filter.

Název v anglickém jazyce

On Nonlinearity Measuring Aspects of Stochastic Integration Filter

Popis výsledku anglicky

The paper deals with Bayesian state estimation of nonlinear stochastic dynamic systems. The focus is aimed at the stochastic integration filter, which is based on a stochastic integration rule. It is shown that the covariance matrix of the integration error calculated as a byproduct of the rule can be used as a measure of nonlinearity. The measure informs the user about validity of the assumptions of Gaussianity, which is adopted by the stochastic integration filter. It is also demonstrated how to use this information for a prediction of the number of remaining iterations of the rule. The paper also focuses on utilization of the integration error covariance matrix for improving estimates of the mean square error of the estimates, which is produced by the filter.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/GC16-19999J" target="_blank" >GC16-19999J: Kooperativní přístupy k návrhu nelineárních filtrů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics

ISBN

978-989-758-198-4

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

9

Strana od-do

353-361

Název nakladatele

Scitepress

Místo vydání

Lisabon

Místo konání akce

Lisabon, Portugal

Datum konání akce

29. 7. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000392610900041