. 2023 Jun 2;17:1124089. doi: 10.3389/fnins.2023.1124089

Table 2.

The detailed network structure of the discriminator $D_{φ}$ and $D_{ψ}$ .

Discriminator	Layers	Input	Output	Kernel	Stride	Activation layer
$D_{φ}$	$Conv 1$	1	10	(1, 23)	(1, 1)	$LeakyReLU$
	$Conv 2$	10	30	(22, 1)	(1, 1)	$LeakyReLU$
	$Conv 3$	30	30	(1, 17)	(1, 1)	$LeakyReLU$
	$Maxpool$	–	–	(1, 6)	(1, 6)	–
	$Conv 4$	30	30	(1, 7)	(1, 7)	$LeakyReLU$
	$Maxpool$	–	–	(1, 6)	(1, 6)	–
	$FC$	750	1	–	–	–
$D_{ψ}$	$Conv 1$	1	10	(1, 23)	(1, 1)	$LeakyReLU$
	$Conv 2$	10	30	(4, 1)	(4, 1)	$LeakyReLU$
	$Conv 3$	30	30	( $Var$ , 1)	(1, 1)	$LeakyReLU$
	$Conv 4$	30	30	(1, 17)	(1, 1)	$LeakyReLU$
	$Maxpool$	–	–	(1, 6)	(1, 6)	–
	$Conv 5$	30	30	(1, 7)	(1, 1)	$LeakyReLU$
	$Maxpool$	–	–	(1, 6)	(1, 6)	–
	$FC$	750	1	–	–	–