EEG Mental Recognition Based on RKHS Learning and Source Dictionary Regularized RKHS Subspace Learning

This article mainly studies Electroencephalogram (EEG) mental recognition. Because the human brain is very complex and the EEG signal is greatly affected by the environment, EEG mental recognition can be attributed to domain adaptative problems. Our main work is as follows: (1) At present, most doma...

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Veröffentlicht in:	IEEE access 2021, Vol.9, p.150545-150559
Hauptverfasser:	Lei, Wenjie, Ma, Zhengming, Liu, Shuyu, Lin, Yuanping
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Algorithms Brain computer interface Competition Complexity Dictionaries domain adaptation learning Domains electroencephalogram Electroencephalography Graphical models Hilbert space Human-computer interface Kernel Kernel functions Machine learning Machine learning algorithms Recognition Regularization Spatial distribution subspace learning Subspaces Task analysis
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