Cognitive Computing for Brain–Computer Interface-Based Computational Social Digital Twins Systems-Reference-Cited by-同舟云学术

Cognitive Computing for Brain–Computer Interface-Based Computational Social Digital Twins Systems

Published:2022-12 Issue:6 Volume:9 Page:1635-1643
ISSN:2329-924X
Container-title:IEEE Transactions on Computational Social Systems
language:
Short-container-title:IEEE Trans. Comput. Soc. Syst.

Author:

Lv Zhihan¹^ORCID,Qiao Liang²^ORCID,Lv Haibin³^ORCID

Affiliation:

1. Faculty of Arts, Uppsala University, Uppsala, Sweden

2. College of Computer Science & Technology, Qingdao University, Qingdao, China

3. Ministry of Natural Resources of the People’s Republic of China North China Sea Bureau, North China Sea Offshore Engineering Survey Institute, Qingdao, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/6570650/9966856/09887930.pdf?arnumber=9887930

Reference35 articles.

1. Learning joint space–time–frequency features for EEG decoding on small labeled data

2. Motor Imagery EEG Decoding Method Based on a Discriminative Feature Learning Strategy

3. Riemannian Procrustes Analysis: Transfer Learning for Brain–Computer Interfaces

4. Tangent Space Features-Based Transfer Learning Classification Model for Two-Class Motor Imagery Brain–Computer Interface

5. Decoding Analysis of Alpha Oscillation Networks on Maintaining Driver Alertness

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