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Computational Intelligence and Neuroscience
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Computational Intelligence and Neuroscience
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2019
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Article
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Tab 3
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Research Article
Driving Fatigue Detection from EEG Using a Modified PCANet Method
Table 3
The average time (seconds) used in the feature extraction, model training, and testing between the traditional PCANet and the proposed modified PCANet method.
Steps
Methods
Number of PCA filters
2
4
6
8
10
12
Features extraction
Modified-PCANet
ā
0.89
1.46
2.18
2.91
4.22
7.71
PCANet
ā
125.43
219.94
320.39
449.50
651.95
1202.40
Model training
Modified-PCANet
SVM
0.05
0.70
5.67
10.34
13.25
15.65
KNN
0.02
0.30
2.20
4.10
5.12
6.15
PCANet
SVM
7.02
126.66
302.52
736.79
1813.40
3606.80
KNN
2.70
49.01
118.60
285.04
697.46
1387.23
Model testing
Modified-PCANet
SVM
0.25
0.26
0.26
0.28
0.34
0.39
KNN
0.10
0.12
0.13
0.15
0.13
0.16
PCANet
SVM
1.16
2.94
5.34
11.10
20.84
35.75
KNN
0.45
1.14
2.10
4.22
8.02
14.06