Neighborhood based decision theoretic rough set under dynamic granulation for BCI motor imagery classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Human-Computer Interaction,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s12193-020-00358-4.pdf
Reference58 articles.
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3. Luo J, Wang J, Rong X, Kailiang X (2019) Class discrepancy-guided sub band filter-based common spatial pattern for motor imagery classification. J Neurosci Methods 323:98–107
4. Li D, Zhang H, Khan MS, Mi F (2018) A self-adaptive frequency selection common spatial pattern and least squares twin support vector machine for motor imagery electroencephalography recognition. Biomed Signal Process Control 42:222–232
5. Jana GC, Swetapadma A, Pattnaik PK (2018) Enhancing the performance of motor imagery classification to design a robust brain computer interface using feed forward back-propagation neural netpaper. Ain Shams Eng J 9(4):2871–2878
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