A multi-mode cantilever singular point detection using adaptive hypothesis testing

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dc.contributor.authorDokoupil, Jakubcs
dc.contributor.authorVáclavek, Pavelcs
dc.coverage.issue1cs
dc.coverage.volume633cs
dc.date.issued2015-10-05cs
dc.description.abstractFundamental analysis of a multi-mode model of the atomic force microscope cantilever shows that at some points; called here singular points, the mode is vanished. Consequently, the order of the input/output behavior is reduced. The singular points can be detected comparing possible candidates on the best model order. The detection is then naturally performed by applying the Bayesian model comparison. Since the exact position of the singular points is not available a priori, an explicit model of updating the probability of tested hypotheses in time is built. More specifically, a mechanism of suppressing absolute information is suggested based on the Bayesian decision problem where the Kullback-Leibler divergence is used.en
dc.description.abstractFundamental analysis of a multi-mode model of the atomic force microscope cantilever shows that at some points; called here singular points, the mode is vanished. Consequently, the order of the input/output behavior is reduced. The singular points can be detected comparing possible candidates on the best model order. The detection is then naturally performed by applying the Bayesian model comparison. Since the exact position of the singular points is not available a priori, an explicit model of updating the probability of tested hypotheses in time is built. More specifically, a mechanism of suppressing absolute information is suggested based on the Bayesian decision problem where the Kullback-Leibler divergence is used.en
dc.formattextcs
dc.format.extent1-4cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationJournal of Physics: Conference Series. 2015, vol. 633, issue 1, p. 1-4.en
dc.identifier.doi10.1088/1742-6596/633/1/012057cs
dc.identifier.isbn1742-6588cs
dc.identifier.issn1742-6588cs
dc.identifier.orcid0000-0001-7505-8571cs
dc.identifier.orcid0000-0001-8624-5874cs
dc.identifier.other117760cs
dc.identifier.researcheridA-7125-2013cs
dc.identifier.researcheridA-3448-2009cs
dc.identifier.scopus55807219000cs
dc.identifier.scopus8448897700cs
dc.identifier.urihttp://hdl.handle.net/11012/137102
dc.language.isoencs
dc.publisherIOP Publishingcs
dc.relation.ispartofJournal of Physics: Conference Seriescs
dc.relation.urihttp://iopscience.iop.org/article/10.1088/1742-6596/633/1/012057cs
dc.rightsCreative Commons Attribution 3.0 Unportedcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1742-6588/cs
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/cs
dc.subjecthypothesis testingen
dc.subjectBayesian methodsen
dc.subjectadaptive systemsen
dc.subjecthypothesis testing
dc.subjectBayesian methods
dc.subjectadaptive systems
dc.titleA multi-mode cantilever singular point detection using adaptive hypothesis testingen
dc.title.alternativeA multi-mode cantilever singular point detection using adaptive hypothesis testingen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-117760en
sync.item.dbtypeVAVen
sync.item.insts2025.10.14 15:17:49en
sync.item.modts2025.10.14 10:49:31en
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Kybernetika pro materiálové vědycs
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