Enhancing Dynamic-Mode Decomposition via Multi-Scale Analysis

Abstract

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.