Algorithm 1 Interpolation and Rescaling in Norm&Location.

Input:  The input data ${\left\{x_l\right\}}_{l=1}^L$; ${\left\{U_{{\epsilon }_j}\right\}}_{j=1}^J$, where J is the total number of processed data, ${\epsilon }_j=\left\{t_{s,j},t_{e,j}\right\}$; alignment quantity $\vartheta$; 1:for each $U_{{\epsilon }_j}$ do 2:   List all $U_{{\epsilon }_j}$ in chronological order; 3:   Compute sampling interval $s=⌈\left(t_{s,j}-t_{e,j}\right)/\vartheta ⌉$, interpolation quantity $J=\vartheta s$; 4:   Sample J points based on linear interpolation using the two neighbors of each point $g=\left[t_s+\frac{k(t_{s,j}-t_{e,j})}{J}forkinrange\left(J\right)\right]$; 5:   $X_{in}=[\left(⌈i⌉-i\right)x_{\lfloor i\rfloor }+\left(i-⌊i⌋\right)x_{\lceil i\rceil } foriing]$; 6:   $y_{{\epsilon }_j}=\left[mean\left(X_{in}\left[ks:\left[k+1\right]s\right]\right) forkinrange\left(\vartheta \right)\right]$; 7:end for Output:  $Y={\left\{y_{{\epsilon }_j}\right\}}_{j=1}^J$.