TABLE 2.

Summary of the discriminator.

Layer	Method	Parameter	Value
InputLayer_1	Label input	Shape	(None, One-hot label)
Dense_1	—	Units	Window
		Activation	LeakyReLU
Reshape_1	—	Output	(None, Window, 1)
InputLayer_2	Mixed EEGs input	Shape	(None, Window, Channels)
Concatenate_1	Reshape_1 & InputLayer_2	Axis	2
Conv1D_1	Temporal dimension	Filters	16
		Kernel Size	32
		Stride	1
		Activation	LeakyReLU
Conv1D_2	Temporal dimension	Filters	8
		Kernel Size	16
		Stride	1
		Activation	LeakyReLU
Conv1D_3	Temporal dimension	Filters	4
		Kernel Size	8
		Stride	1
		Activation	LeakyReLU
Conv1D_4	Temporal dimension	Filters	2
		Kernel Size	4
		Stride	1
		Activation	LeakyReLU
Flatten_1	—	—	—
Dropout_1	—	Value	0.4
Dense_2	—	Units	1
		Activation	sigmoid
Loss Function	Binary Cross entropy	—	—
Optimizer	RMSprop	Learning rate	0.0008
		Clip value	1.0
		Decay	1e-8
		Activation	Tanh