Table 1.
Parameters of each layer of proposed 1D convolutional neural network (CNN).
| Layers | Parameters | Activation |
|---|---|---|
| Conv1D | Filter 32/kernel 5 | ReLU |
| BN | ||
| Maxpooling | 2 | |
| Conv1D | Filter 32/kernel 5 | ReLU |
| Maxpooling | 2 | |
| Conv1D | Filter 64/kernel 5 | ReLU |
| Maxpooling | 2 | |
| Conv1D | Filter 64/kernel 5 | ReLU |
| Maxpooling | 2 | |
| Conv1D | Filter 128/kernel 5 | ReLU |
| Maxpooling | 2 | |
| Conv1D | Filter 128/kernel 5 | ReLU |
| Maxpooling | 2 | |
| Dropout | 0.5 | |
| Conv1D | Filter 256/kernel 5 | ReLU |
| Maxpooling | 2 | |
| Conv1D | Filter 256/kernel 5 | ReLU |
| Maxpooling | 2 | |
| Dropout | 0.5 | |
| Conv1D | Filter 512/kernel 5 | ReLU |
| Maxpooling | 2 | |
| Dropout | 0.5 | |
| Conv1D | Filter 512/kernel 5 | ReLU |
| Flatten | ||
| Dense | 128 | ReLU |
| Dropout | 0.5 | |
| Dense | 32 | ReLU |
| Dense | 4 | Softmax |