Feature Selection and Classification of EEG Finger Movement Based on Genetic Algorithm

dc.contributor.author	Al Dabag, M.L.
dc.contributor.author	Ozkurt, N.
dc.contributor.author	Najeeb, S.M.M.
dc.date.accessioned	2021-01-25T19:33:09Z
dc.date.available	2021-01-25T19:33:09Z
dc.date.issued	2018
dc.identifier.uri	https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/7581
dc.description.abstract	Electroencephalography (EEG) classification for mental tasks is the crucial part of the brain-computer interface. Many studies try to extract discriminative features from EEG signals. In this study, feature selection algorithm based on genetic algorithm (
dc.language.iso	English
dc.publisher	IEEE
dc.title	Feature Selection and Classification of EEG Finger Movement Based on Genetic Algorithm
dc.type	Proceedings Paper
dc.relation.firstpage	24
dc.relation.lastpage	28
dc.description.woscategory	Computer Science, Artificial Intelligence; Computer Science, Theory & Methods; Engineering, Electrical & Electronic
dc.description.wosresearcharea	Computer Science; Engineering
dc.identifier.wosid	WOS:000455592800028
dc.identifier.ctitle	Innovations in Intelligent Systems and Applications Conference (ASYU)
dc.identifier.cdate	OCT 04-06, 2018

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