Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Ruijing Lin"'
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
BackgroundThe development of Brain-Computer Interface (BCI) technology has brought tremendous potential to various fields. In recent years, prominent research has focused on enhancing the accuracy of BCI decoding algorithms by effectively utilizing m
Externí odkaz:
https://doaj.org/article/516b4a0d6fd947fe826f044e131fad30
Publikováno v:
IRBM. 44:100781
Publikováno v:
Computational intelligence and neuroscience. 2022
When a brain-computer interface (BCI) is designed, high classification accuracy is difficult to obtain for motor imagery (MI) electroencephalogram (EEG) signals in view of their relatively low signal-to-noise ratio. In this paper, a fused multidimens
Autor:
Pengfei Ma, Chaoyi Dong, Shuang Ma, Tingting Jia, Zhiyun Xiao, Yongsheng Qi, Xiaoyan Chen, Ruijing Lin
Publikováno v:
2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP).
Autor:
Pengfei Ma, Chaoyi Dong, Ruijing Lin, Shuang Ma, Tingting Jia, Xiaoyan Chen, Zhiyun Xiao, Yongsheng Qi
Publikováno v:
Journal of neuroscience methods. 371
In the study of brain-computer interfaces (BCIs) based on steady-state visual evoked potentials (SSVEPs), how to improve the classification accuracies of BCIs has always been the focus of researchers. Canonical correlation analysis (CCA) is widely us