Name
Title | ||
|---|---|---|
Deep stacked support matrix machine based representation learning for motor imagery EEG classification. |
Abstract | ||
|---|---|---|
•Novel deep stacked support matrix machine (DSSMM) for EEG classification.•DSSMM combines the virtue of SMM with the powerful feature representation derived from the deep architecture.•DSSMM can improve the classification performance of motor imagery EEG data. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.cmpb.2020.105466 | Computer Methods and Programs in Biomedicine |
Keywords | DocType | Volume |
Electroencephalograph,brain-computer interface,support matrix machine,stacked generalization,deep architecture | Journal | 193 |
ISSN | Citations | PageRank |
0169-2607 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenlong Hang | 1 | 5 | 2.12 |
| Wei Feng | 2 | 0 | 0.34 |
| Shuang Liang | 3 | 7 | 8.41 |
| Qiong Wang | 4 | 30 | 15.18 |
| Xuejun Liu | 5 | 0 | 0.34 |
| Kup-Sze Choi | 6 | 526 | 47.41 |