Regularized RKHS-Based Subspace Learning for Motor Imagery Classification

Regularized RKHS-Based Subspace Learning for Motor Imagery Classification

Brain–computer interface (BCI) technology allows people with disabilities to communicate with the physical environment. One of the most promising signals is the non-invasive electroencephalogram (EEG) signal. However, due to the non-stationary nature of EEGs, a subject’s signal may change over time,...

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Bibliographic Details
Main Authors: Linzhi Jiang, Shuyu Liu, Zhengming Ma, Wenjie Lei, Cheng Chen
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Entropy
Subjects:
EEG
brain–computer interfaces
domain adaptation
reproducing kernel Hilbert space
SLDA
Online Access:https://www.mdpi.com/1099-4300/24/2/195

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https://www.mdpi.com/1099-4300/24/2/195

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