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A New Subject-Specific Discriminative and Multi-Scale Filter Bank Tangent Space Mapping Method for Recognition of Multiclass Motor Imagery

by Wu, Fan, Gong, Anmin, Li, Hongyun, Zhao, Lei, Zhang, Wei, Fu, Yunfa
Published in Frontiers in human neuroscience (08.03.2021)

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Riemannian classifier enhances the accuracy of machine-learning-based diagnosis of PTSD using resting EEG

by Kim, Yong-Wook, Kim, Sungkean, Shim, Miseon, Jin, Min Jin, Jeon, Hyeonjin, Lee, Seung-Hwan, Im, Chang-Hwan
Published in Progress in neuro-psychopharmacology & biological psychiatry (30.08.2020)

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움직임 상상 기반 뇌-컴퓨터 인터페이스를 위한 운동 심상, 실행, 관찰 뇌파 비교 분석

by 권다은, 황민주, 권지현, 신예은, 안민규, Daeun, Gwon, Minjoo, Hwang, Jihyun, Kwon, Yeeun, Shin, Minkyu, Ahn
Published in Journal of biomedical engineering research (2022)

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Modern machine learning algorithms to classify cognitive and affective states from electroencephalography signals

by Appriou, Aurélien, Cichocki, Andrzej, Lotte, Fabien
Published in IEEE systems, man, and cybernetics magazine (01.02.2020)

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A New Subject-Specific Discriminative and Multi-Scale Filter Bank Tangent Space Mapping Method for Recognition of Multiclass Motor Imagery

Riemannian classifier enhances the accuracy of machine-learning-based diagnosis of PTSD using resting EEG

움직임 상상 기반 뇌-컴퓨터 인터페이스를 위한 운동 심상, 실행, 관찰 뇌파 비교 분석

Modern machine learning algorithms to classify cognitive and affective states from electroencephalography signals

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