Gao, Y.; Si, J.; Wu, S.; Li, W.; Liu, H.; Chen, J.; He, Q.; Zhang, Y.
Improvement of the Classification Accuracy of Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces by Combining L1-MCCA with SVM. Appl. Sci. 2021, 11, 11453.
https://doi.org/10.3390/app112311453
AMA Style
Gao Y, Si J, Wu S, Li W, Liu H, Chen J, He Q, Zhang Y.
Improvement of the Classification Accuracy of Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces by Combining L1-MCCA with SVM. Applied Sciences. 2021; 11(23):11453.
https://doi.org/10.3390/app112311453
Chicago/Turabian Style
Gao, Yuhang, Juanning Si, Sijin Wu, Weixian Li, Hao Liu, Jianhu Chen, Qing He, and Yujin Zhang.
2021. "Improvement of the Classification Accuracy of Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces by Combining L1-MCCA with SVM" Applied Sciences 11, no. 23: 11453.
https://doi.org/10.3390/app112311453
APA Style
Gao, Y., Si, J., Wu, S., Li, W., Liu, H., Chen, J., He, Q., & Zhang, Y.
(2021). Improvement of the Classification Accuracy of Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces by Combining L1-MCCA with SVM. Applied Sciences, 11(23), 11453.
https://doi.org/10.3390/app112311453
