Student-t process quadratures for filtering of non-linear systems with heavy-tailed noise

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Prüher, Jakub
dc.contributor.author Tronarp, Filip
dc.contributor.author Karvonen, Toni
dc.contributor.author Särkkä, Simo
dc.contributor.author Straka, Ondrej
dc.date.accessioned 2017-11-21T13:36:10Z
dc.date.available 2017-11-21T13:36:10Z
dc.date.issued 2017-07
dc.identifier.citation Prüher , J , Tronarp , F , Karvonen , T , Särkkä , S & Straka , O 2017 , Student-t process quadratures for filtering of non-linear systems with heavy-tailed noise . in 20th International Conference on Information Fusion, Fusion 2017 - Proceedings . Institute of Electrical and Electronics Engineers Inc. , pp. 875-882 , International Conference on Information Fusion , Xian , China , 10-13 July . DOI: 10.23919/ICIF.2017.8009742 en
dc.identifier.isbn 978-0-9964-5270-0
dc.identifier.other PURE UUID: 5942cc0d-1ff9-45fa-bf7f-16c69d664be8
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/studentt-process-quadratures-for-filtering-of-nonlinear-systems-with-heavytailed-noise(5942cc0d-1ff9-45fa-bf7f-16c69d664be8).html
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/15868096/PruherEtal2017_FUSION.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/28794
dc.description.abstract 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. en
dc.format.extent 8
dc.format.extent 875-882
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartof International Conference on Information Fusion en
dc.relation.ispartofseries 20th International Conference on Information Fusion, Fusion 2017 - Proceedings en
dc.rights openAccess en
dc.subject.other 111 Mathematics en
dc.subject.other 113 Computer and information sciences en
dc.title Student-t process quadratures for filtering of non-linear systems with heavy-tailed noise en
dc.type A4 Artikkeli konferenssijulkaisussa fi
dc.description.version Peer reviewed en
dc.contributor.department University of West Bohemia
dc.contributor.department Department of Electrical Engineering and Automation
dc.subject.keyword 111 Mathematics
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201711217615
dc.identifier.doi 10.23919/ICIF.2017.8009742
dc.type.version acceptedVersion


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