Non-negative matrix factorization for EEG

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86089241" target="_blank" >RIV/61989100:27240/13:86089241 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/TAEECE.2013.6557219" target="_blank" >http://dx.doi.org/10.1109/TAEECE.2013.6557219</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TAEECE.2013.6557219" target="_blank" >10.1109/TAEECE.2013.6557219</a>

Result language
angličtina
Original language name
Non-negative matrix factorization for EEG
Original language description
Today with the progress of science and technology becomes signal analysis, data analysis and data mining are very Important in most science and engineering applications. Extracting useful knowledge from experimental raw datasets, measurements, observations and analysis and understand complex data has become very important challenge in the world. The raw datasets in most common is collected from complex phenomena that express to integrated result of various hidden related variables or they are set of underlying hidden component of factors. The complex raw dataset first must be decomposition by dimensionally reduction method such as matrix decomposition to extraction the hidden information or hidden factors of complex raw dataset.
Czech name
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Czech description
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Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2013 INTERNATIONAL CONFERENCE ON TECHNOLOGICAL ADVANCES IN ELECTRICAL, ELECTRONICS AND COMPUTER ENGINEERING (TAEECE)
ISBN
978-1-4673-5613-8
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
183-187
Publisher name
IEEE
Place of publication
New York
Event location
Konya
Event date
May 9, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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