TABLE 3.
Separable convolutional neural network (SepCNN) architecture for within-participant recognition.
Layer | Kernel | Size | Options | Output |
Input | 200 × 30 | |||
BatchNorm1D | 200 × 30 | |||
DepthConv1D | 30 | 10 | Stride = 6, Padding = 4 | 34 × 30 |
BatchNorm1D | 34 × 30 | |||
PointConv1D | 4 | 1 | Stride = 1, Padding = 0 | 34 × 4 |
Activation | Tanh | 34 × 4 | ||
Flatten | 136 | |||
Activation | Sigmoid | 1 |