# State-Of-The-Art Algorithms For Low-Rank Dynamic Mode Decomposition

**Authors:** Patrick Heas, Cedric Herzet  
**arXiv:** [2108.09160](https://arxiv.org/abs/2108.09160)  
**Date:** 2021-08-20  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2108.09160v1/

## Abstract

This technical note reviews sate-of-the-art algorithms for linear approximation of high-dimensional dynamical systems using low-rank dynamic mode decomposition (DMD). While repeating several parts of our article "low-rank dynamic mode decomposition: an exact and tractable solution", this work provides additional details useful for building a comprehensive picture of state-of-the-art methods.