Name
Abstract | ||
|---|---|---|
Electroencephalogram (EEG) classification is one of the most important research topics of Brain Computer Interface (BCI). In this paper, a novel method based on broad learning system and composite features (CF-Bls) is proposed to deal with EEG data. Firstly, EEG signals are divided into 1-second ‘frames’ and mapped into 2D images. Then, Gabor filters are used to extract the texture features of the... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/SPAC53836.2021.9539966 | 2021 International Conference on Security, Pattern Analysis, and Cybernetics（SPAC) |
Keywords | DocType | ISBN |
Learning systems,Wavelet transforms,Convolution,Feature extraction,Electroencephalography,Brain-computer interfaces,Classification algorithms | Conference | 978-1-6654-4322-7 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lincan Xu | 1 | 0 | 0.34 |
| Junwei Duan | 2 | 0 | 0.34 |
| Yujuan Quan | 3 | 0 | 0.34 |
| Zhiguo Zhou | 4 | 0 | 0.34 |