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math.NA2026

On residual bounds of the EDMD solution to the eigenvalue problem for the Koopman operator and backward shadowing stability of the EDMD/KMD

Zlatko Drmač, Zlatko Drmač

This paper introduces shadowing theory based backward stability assessment of data driven computational analysis of discrete dynamical systems in the framework of the Koopman compo…

math.NA2026

New Robust Streaming DMD with Forecasting

Zlatko Drmač, Ela Đimoti

The Dynamic Mode Decomposition (DMD) and the more general Extended DMD (EDMD) are powerful tools for computational analysis of dynamical systems in data-driven scenarios. They are…

math.NA2025

An Introductory Guide to Koopman Learning

Matthew J. Colbrook, Zlatko Drmač, Andrew Horning

Koopman operators provide a linear framework for data-driven analyses of nonlinear dynamical systems, but their infinite-dimensional nature presents major computational challenges.…

math.NA2024

A data driven Koopman-Schur decomposition for computational analysis of nonlinear dynamics

Zlatko Drmač, Igor Mezić

This paper introduces a new theoretical and computational framework for a data driven Koopman mode analysis of nonlinear dynamics. To alleviate the potential problem of ill-conditi…

math.NA2024

IRKA is a Riemannian Gradient Descent Method

Petar Mlinarić, Christopher A. Beattie, Zlatko Drmač +1

The iterative rational Krylov algorithm (IRKA) is a commonly used fixed-point iteration developed to minimize the model order reduction error. In this work, IRKA is…