ICA decomposition as a basis for finding hidden EEG structures by dimension reduction methods

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F19%3A00336898" target="_blank" >RIV/68407700:21460/19:00336898 - isvavai.cz</a>
Result on the web
<a href="http://poseidon2.feld.cvut.cz/conf/poster/" target="_blank" >http://poseidon2.feld.cvut.cz/conf/poster/</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
ICA decomposition as a basis for finding hidden EEG structures by dimension reduction methods
Original language description
Electroencephalography (EEG) is the electrical signal of the brain whose analysis makes it possible to recognize its pathologies and brain diseases. EEG signal is very complex, hence for better understanding several linear and non-linear processing techniques are widely used to help to detect the hidden data structure. The aim of this study is to test linear and nonlinear dimensional reduction to obtain information about the internal hidden data structure. Based on this information, suitable properties for describing the EEG signal can be determined. Our method seems to be working out well for alpha activity and eye activity space examination.
Czech name
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Czech description
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Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the International Student Scientific Conference Poster – 23/2019
ISBN
978-80-01-06581-5
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
ČVUT FEL, Středisko vědecko-technických informací
Place of publication
Praha
Event location
ČVUT FEL, Technická 2, Praha 6
Event date
May 23, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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