Figure 2.

Details of the discriminator in the WGAN-EEG. We followed the architectural guidelines for the discriminator to use the LeakyReLU activation function and avoid max-pooling along the network. The discriminator network contains eight convolutional layers with an increasing number of filter kernels by a factor of 2. After eight convolutional layers, there are two FCN layers, of which the first layer has 1,024 outputs with the LeakyReLU activation function, and the second layer has a single output. Following the instructions of the WGAN, the discriminator of the WGAN-EEG has no sigmoid cross entropy layer.