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https://hdl.handle.net/11147/9869
Title: | Automated labeling of electroencephalography data using quasi-supervised learning | Authors: | Köktürk, Başak Esin Karaçalı, Bilge |
Keywords: | Electroencephalogram independent component analysis quasi-supervised learning wavelet transform |
Issue Date: | 2012 | Publisher: | Institute of Electrical and Electronics Engineers Inc. | Abstract: | In this study, the separation of the stimulus effects from the baseline was investigated in electroencephalography data recorded under different visual stimuli using quasi-supervised learning. The data feature vectors were constructed using independent component analysis and wavelet transform, and then, these feature vectors were separated using quasi-supervised learning. Experiment results showed that the EEG data of the stimuli can be separated using quasi-supervised learning. © 2012 IEEE. | URI: | https://doi.org/10.1109/SIU.2012.6204600 https://hdl.handle.net/11147/9869 |
ISBN: | 9.78E+12 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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