Motor Imagery BCI Classification Based on Multivariate Variational Mode Decomposition-Reference-Cited by-同舟云学术

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Motor Imagery BCI Classification Based on Multivariate Variational Mode Decomposition

Published:2022-10 Issue:5 Volume:6 Page:1177-1189
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Sadiq Muhammad Tariq¹^ORCID,Yu Xiaojun¹^ORCID,Yuan Zhaohui¹^ORCID,Aziz Muhammad Zulkifal¹^ORCID,Rehman Naveed ur²^ORCID,Ding Weiping³^ORCID,Xiao Gaoxi⁴^ORCID

Affiliation:

1. School of Automation, Northwestern Polytechnical University, Xi’an, China

2. Department of Electrical and Computer Engineering, Aarhus University, Aarhus, Denmark

3. School of Information and Technology, Nantong University, Nantong, China

4. Nanyang Technological University, Singapore

Funder

Key Research and Development Program of Shaanxi

China Postdoctoral Science Foundation

Shaanxi Province Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computational Mathematics,Control and Optimization,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7433297/9900106/09714727.pdf?arnumber=9714727

Reference55 articles.

1. Ictal EEG classification based on amplitude and frequency contours of IMFs;biju;Journal of Biocybernetics and Biomedical Engineering,2017

2. A multistage knowledge-based system for EEG seizure detection in newborn infants

3. 10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems

4. Multivariate Variational Mode Decomposition

5. Motor Imagery EEG Signals Decoding by Multivariate Empirical Wavelet Transform-Based Framework for Robust Brain–Computer Interfaces

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