$\mathcal{T}$	Classification task
$\mathcal{D}$	a specific domain
${\mathcal{D}}^{\mathcal{S}},{\mathcal{D}}^{\mathcal{T}}$	Source domain and target domain
$\mathcal{X}$	Input sample space
$\mathcal{Y}$	Input label space
${\mathcal{X}}^{\mathcal{S}},{\mathcal{X}}^{\mathcal{T}}$	Input source sample space and target sample space
${\mathcal{Y}}^{\mathcal{S}},{\mathcal{Y}}^{\mathcal{T}}$	Input label sample space and target label space
$X,Y$	Dataset and labels
$\mathit{x},\mathit{y}$	a sample and a label in dataset
Z	Learned features representation
$g(·)$	Feature extractor of deep learning model
$h(·)$	Classifier of deep learning model
${\ell }_{clf},d(·)$	classification loss and domain loss
$G(·)$	a convolution operation
$A\left(f_i\right)$	Amplitude frequency characteristic of $G(·)$ under frequency $f_i$