  Through the use of wavelet based Besov norms, we compute nontrivial
multiscale nonlinear features of a given data set so as to enhance the standard
Dynamic-Mode Decomposition algorithm. Thus we are able to build sophisticated
observables which enhance algorithm performance without placing undue
computational burdens on the user.
