Multi-class motor imagery EEG classification using collaborative representation-based semi-supervised extreme learning machine-Reference-Cited by-同舟云学术

Multi-class motor imagery EEG classification using collaborative representation-based semi-supervised extreme learning machine

Published:2020-07-16 Issue:9 Volume:58 Page:2119-2130
ISSN:0140-0118
Container-title:Medical & Biological Engineering & Computing
language:en
Short-container-title:Med Biol Eng Comput

Author:

She Qingshan^ORCID,Zou Jie,Luo Zhizeng,Nguyen Thinh,Li Rihui,Zhang Yingchun

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Biomedical Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11517-020-02227-4.pdf

Reference37 articles.

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3. Lotte F, Bougrain L, Cichocki A, Clerc M, Congedo M, Rakotomamonjy A, Yger F (2018) A review of classification algorithms for eeg-based brain-computer interfaces: a 10-year update. J Neural Eng 15:031005

4. Ma YL, She QS et al (2016) Classification of motor imagery eeg signals with support vector machines and particle swarm optimization. Comput Math Methods Med 4941235

5. Li RH et al (2017) Enhancing performance of a hybrid EEG-fNIRS system using channel selection and early temporal features. Front Hum Neurosci 11:462

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