Student-t Process Quadratures for Filtering of Non-Linear Systems with Heavy-Tailed Noise
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43949729" target="_blank" >RIV/49777513:23520/17:43949729 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.23919/ICIF.2017.8009742" target="_blank" >http://dx.doi.org/10.23919/ICIF.2017.8009742</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/ICIF.2017.8009742" target="_blank" >10.23919/ICIF.2017.8009742</a>
Alternative languages
Result language
angličtina
Original language name
Student-t Process Quadratures for Filtering of Non-Linear Systems with Heavy-Tailed Noise
Original language description
The aim of this article is to design a moment transformation for Student-t distributed random variables, which is able to account for the error in the numerically computed mean. We employ Student-t process quadrature, an instance of Bayesian quadrature, which allows us to treat the integral itself as a random variable whose variance provides information about the incurred integration error. Advantage of the Student-t process quadrature over the traditional Gaussian process quadrature, is that the integral variance depends also on the function values, allowing for a more robust modelling of the integration error. The moment transform is applied in nonlinear sigma-point filtering and evaluated on two numerical examples, where it is shown to outperform the state-of-the-art moment transforms.
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
20205 - Automation and control systems
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
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 International Conference on Information Fusion
ISBN
978-0-9964527-0-0
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
875-882
Publisher name
IEEE
Place of publication
Xi'an
Event location
Xi'an, China
Event date
Jul 10, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000410938300124