The experimental, exact, pretrained DNN, and trained DNN impedances for each 2×ZARC model are displayed on the right panel of Figure . We found that the trained DNN DRT was much closer to the exact DRT than the pretrained DNN DRT (Figure ). This was validated with the DNN error for RR ( 𝜀 , = 24.33%, 41.95%, and 44.49% for the overlapping, separated, and distant 2×ZARC models, respectively, see Table ) and for DNN training (𝜀 , ≈ 6.60%, 6.75%, and 13.59%). Moreover, the trained DNN slightly improved the impedance recovery, as shown in Figure and by the impedance errors for RR (𝜀̅ , ≈ 3.28%, 5.48%, and 5.34%, see Table ) and for DNN training (𝜀̅ , ≈ 3.22%, 2.12%, and 2.12%).