Table of Content

Open Access iconOpen Access

ABSTRACT

Kalman Filter Dynamic Mode Decomposition for Data Assimilation

Taku Nonomura

Tohoku University, Aoba 6-6-01, Aramaki, Aoba, Sendai, 980-8579, Japan.
Corresponding Author: Taku Nonomura. Email: nonomura@aero.mech.tohoku.ac.jp.

The International Conference on Computational & Experimental Engineering and Sciences 2019, 21(4), 73-74. https://doi.org/10.32604/icces.2019.05266

Abstract

In this presentation, a family of Kalman filter dynamic mode decomposition, which consists of algorithms of the linear Kalman filter DMD method which identify the linear system and the extended Kalman filter DMD method which simultaneously identify the system and estimates state variable, is introduced. Then, the application of the extended Kalman filter DMD to data assimilation is discussed.

Keywords


Cite This Article

Nonomura, T. (2019). Kalman Filter Dynamic Mode Decomposition for Data Assimilation. The International Conference on Computational & Experimental Engineering and Sciences, 21(4), 73–74.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1108

    View

  • 821

    Download

  • 0

    Like

Share Link