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Enhancing performance of subject-specific models via subject-independent information for SSVEP-based BCIs

Enhancing performance of subject-specific models via subject-independent information for... http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png PLoS ONE Public Library of Science (PLoS) Journal

Enhancing performance of subject-specific models via subject-independent information for SSVEP-based BCIs

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References (47)

Publisher
Public Library of Science (PLoS) Journal
Copyright
Copyright: © 2020 Mehdizavareh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The data that support the findings of this study are openly available at "ftp://sccn.ucsd.edu/pub/ssvep_benchmark_dataset/. Further questions can be directed to the data owners here: Yijun Wang: wangyj@semi.ac.cn Xiaogang Chen: chenxg@bme.cams.cn Xiaorong Gao: gxrdea@tsinghua.edu.cn Shangkai Gao: gsk-dea@tsinghua.edu.cn Funding: The authors received no specific funding for this work. Competing interests: The authors have declared that no competing interests exist.
eISSN
1932-6203
DOI
10.1371/journal.pone.0226048
Publisher site
See Article on Publisher Site

Abstract

Journal

PLoS ONEPublic Library of Science (PLoS) Journal

Published: Jan 14, 2020

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