Description | Value |
---|---|
Generator G | |
Conditioning network | |
Size of latent vector Z | 2*1 |
Rolling window b | 100 |
Forward window f | 10 |
1D Conv layers | 4 |
Input and output channels in all Conv layers | 2*1 |
Dense layer output size | 1 |
Simulator network | |
Dense layer output size | f*1 |
Transpose Conv layers | 2 |
Input channels in the first transpose Conv layer | 4*1 |
Output channels in the first transpose Conv layer | 2*1 |
Input channels in the second transpose Conv layer | 2*1 |
Output channels in the second transpose Conv layer | 1 |
Conditioning and Simulator networks | |
Layers’ activation function | Relu |
Conv and transpose conv kernel length | 5 |
Conv and transpose conv stride | 2 |
Discriminator D | |
Convolution layers | 4 |
Input channels for the kth Conv layer | \(2^{k - 1}\) |
Output channels for the kth Conv layer | \(2^{k}\) |
Layers’ activation function | Leaky_Relu |
Conv and transpose conv kernel length | 5 |
Conv and transpose conv stride | 2 |