A hierarchical semi-supervised extreme learning machine method for EEG recognition-Reference-Cited by-同舟云学术

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A hierarchical semi-supervised extreme learning machine method for EEG recognition

Published:2018-07-28 Issue:1 Volume:57 Page:147-157
ISSN:0140-0118
Container-title:Medical & Biological Engineering & Computing
language:en
Short-container-title:Med Biol Eng Comput

Author:

She Qingshan,Hu Bo,Luo Zhizeng,Nguyen Thinh,Zhang Yingchun^ORCID

Funder

National Nature Science Foundation

Natural Science Foundation of Zhejiang Province

Guangdong Provincial Work Injury Rehabilitation Center

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Biomedical Engineering

Link

http://link.springer.com/article/10.1007/s11517-018-1875-3/fulltext.html

Reference40 articles.

1. Wolpaw J, Wolpaw E W (2012) Brain-computer interfaces: principles and practice. OUP USA

2. Pfurtscheller G, Neuper C (2001) Motor imagery and direct brain-computer communication. Proc IEEE 89(7):1123–1134

3. Sanei S, Chambers J A (2013) EEG signal processing. John Wiley & Sons

4. Samek W, Kawanabe M, Müller KR (2014) Divergence-based framework for common spatial patterns algorithms. IEEE Rev Biomed Eng 7:50–72

5. She Q, Gan H, Ma Y et al (2016) Scale-dependent signal identification in low-dimensional subspace: motor imagery task classification. Neural Plast 7431012

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