Random Subspace Ensemble Learning for Functional Near-Infrared Spectroscopy Brain-Computer Interfaces

Random Subspace Ensemble Learning for Functional Near-Infrared Spectroscopy Brain-Computer Interfaces

The feasibility of the random subspace ensemble learning method was explored to improve the performance of functional near-infrared spectroscopy-based brain-computer interfaces (fNIRS-BCIs). Feature vectors have been constructed using the temporal characteristics of concentration changes in fNIRS ch...

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Bibliographic Details
Main Author:	Jaeyoung Shin
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2020-07-01
Series:	Frontiers in Human Neuroscience
Subjects:	brain-computer interface ensemble learning functional near-infrared spectroscopy linear discriminant analysis random subspace support vector machine
Online Access:	https://www.frontiersin.org/article/10.3389/fnhum.2020.00236/full

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