EEG Signal Analysis based on EMD and Discrete Energy Separation Algorithm

but.event.date28.04.2016cs
but.event.titleStudent EEICT 2016cs
dc.contributor.authorPotočňák, Tomáš
dc.date.accessioned2018-07-10T12:48:19Z
dc.date.available2018-07-10T12:48:19Z
dc.date.issued2016cs
dc.description.abstractThis paper deals with spectral analysis of nocturnal EEG signal from apnoea/hypopnea patients. Main goal is to employ methods independent to Fourier Transform, because of nonstationary character of signal, to better description of frequency changes. For this purpose, analysis based on Empirical Mode Decomposition and Discrete Energy Separation Algorithm was tested. This method is similar to commonly used Hilbert Huang Transform, but can provide higher time and frequency resolution due to algorithms based on Teager-Keiser Energy Operator, which can work with very short time window.en
dc.formattextcs
dc.format.extent528-532cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings of the 22nd Conference STUDENT EEICT 2016. s. 528-532. ISBN 978-80-214-5350-0cs
dc.identifier.isbn978-80-214-5350-0
dc.identifier.urihttp://hdl.handle.net/11012/83989
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 22nd Conference STUDENT EEICT 2016en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectnocturnal EEGen
dc.subjectEmpirical Mode Decompositionen
dc.subjectTeager-Keiser Energy Operatoren
dc.subjectDiscrete Energy Separation Algorithmen
dc.titleEEG Signal Analysis based on EMD and Discrete Energy Separation Algorithmen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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