Pattern recognition of epileptic EEG graphoelements with adaptive segmentation, supervised and unsupervised learning algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F12%3A00201617" target="_blank" >RIV/68407700:21460/12:00201617 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1515/bmt-2012-4219" target="_blank" >http://dx.doi.org/10.1515/bmt-2012-4219</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1515/bmt-2012-4219" target="_blank" >10.1515/bmt-2012-4219</a>
Alternative languages
Result language
angličtina
Original language name
Pattern recognition of epileptic EEG graphoelements with adaptive segmentation, supervised and unsupervised learning algorithms
Original language description
The paper deals with pattern recognition of epileptic EEG graphoelements using adaptive segmentation, supervised and unsupervised learning algorithms for identification of EEG graphoelements of the patients with diagnosis epilepsy. The applications of cluster analysis, k-NN classifier and artificial neural networks were discussed.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů