Omri Azencot, Wotao Yin and Andrea Bertozzi. SIADS 2019. Abstract We propose a new method for computing Dynamic Mode Decomposition (DMD) evolution matrices, which we use to analyze dynamical systems. Unlike the majority of existing methods, our approach is based on a variational formulation consisting of data alignment penalty terms and constitutive orthogonality constraints. Our method does not make any assumptions on the structure of the data or their size, and thus it is applicable to a wide range of problems including nonlinear scenarios or extremely small observation sets. In addition, our technique is robust to noise that is independent…