How can DMD be used to analyze systems evolving on graphs or networks?

The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections ... The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections ... Feb 5, 2021 ... This was coupled with my discovery for Koopman Operator and Dynamic Mode Decomposition which got me thinking about how collecting data on ... In this paper, we will propose an extension of DMD that exploits low-rank tensor decompositions of potentially high-dimensional data sets. Abstract. Originally introduced in the fluid mechanics community, dynamic mode decomposition (DMD) has emerged as a powerful tool for analyzing the dynamics of ... May 8, 2024 ... Title:Multiplicative Dynamic Mode Decomposition ... Abstract:Koopman operators are infinite-dimensional operators that linearize nonlinear ... In this paper, we propose Bayesian DMD, which provides a principled way to transfer the advantages of the Bayesian formulation into DMD. To this end, we first ... Jul 25, 2016 ... The DMD converts a dynamical system into a superposition of modes whose dynamics are governed by eigenvalues. Ryoji Takaki ... A new dynamic mode decomposition (DMD) method is introduced for simultaneous system identification and denoising in conjunction with the adoption ... Mar 21, 2025 ... Using Dynamic Mode Decomposition with control (DMDc), we analyze surface air temperature patterns from climate simulations to elucidate the ...