Brainwave Classification Using Covariance-Based Data Augmentation

A brain-machine interface (BMI) is a technology that controls machines via brainwaves. In BMI, the performance of brainwave analysis is very important for achieving machine control that reflects the user's intention. One of the main obstacles in this analysis is an insufficient amount of data p...

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Veröffentlicht in:	IEEE access 2020, Vol.8, p.211714-211722
Hauptverfasser:	Yang, Wonseok, Nam, Woochul
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial data Brain brain–machine interface Classification classification accuracy Classification algorithms Correlation Covariance matrices Covariance matrix Data augmentation Data points Datasets Gallium nitride Neural networks Parameters Random variables Task analysis Tongue Training
Online-Zugang:	Volltext
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