Forced-Term Modeling in the Koopman Framework for Linear Operator Learning in Nonlinear Dynamical Systems
We study the problem of extracting reliable and interpretable linear models from nonlinear dynamical systems with periodic behavior. Dynamic Mode Decomposition (DMD) is a widely used data-driven method for approximating dynamics by a linear system and is commonly interpreted through Koopman operator theory. However, be...