Flowchart describing the emulation process (from left to right). The N-body simulations first need to be run to provide the matter density distribution for the given DDM parameters and redshift (f, v_k, Γ, z). Next, we extracted power spectra and calculated the resulting power suppression P_DDM/P_ΛCDM. Additionally, we performed PCA on P_DDM/P_ΛCDM data, and using five principal components , we recovered the original power suppression. Once the training data set was prepared, we trained the SIREN-like neural network. We used (f, v_k, Γ, z) as the network input and output five PCA components. The PCA components obtained were used to reconstruct the power spectrum suppressions, which were then compared to the input ones. During the training process, the MSE loss between the input and output power suppression curves was minimised.