Improving Generalization Based on l1-Norm Regularization for EEG-Based Motor Imagery Classification

Improving Generalization Based on l1-Norm Regularization for EEG-Based Motor Imagery Classification

Multichannel electroencephalography (EEG) is widely used in typical brain-computer interface (BCI) systems. In general, a number of parameters are essential for a EEG classification algorithm due to redundant features involved in EEG signals. However, the generalization of the EEG method is often ad...

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Bibliographic Details
Main Authors: Yuwei Zhao, Jiuqi Han, Yushu Chen, Hongji Sun, Jiayun Chen, Ang Ke, Yao Han, Peng Zhang, Yi Zhang, Jin Zhou, Changyong Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-05-01
Series:Frontiers in Neuroscience
Subjects:
motor imagery
electroencephalography (EEG)
classification
l1-norm regularization
generalization
Online Access:http://journal.frontiersin.org/article/10.3389/fnins.2018.00272/full

Internet

http://journal.frontiersin.org/article/10.3389/fnins.2018.00272/full

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