Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session Q01: Nonlinear Dynamics: Model Reduction II
12:50 PM–3:26 PM,
Tuesday, November 20, 2018
Georgia World Congress Center
Room: B201
Chair: Pedram Hassenzadeh, Rice University
Abstract ID: BAPS.2018.DFD.Q01.11
Abstract: Q01.00011 : Improvements on Extended Kalman Filter Dynamic Mode Decomposition for Noisy Dataset*
3:00 PM–3:13 PM
Presenter:
Taku Nonomura
(Tohoku Univ, Presto, JST)
Author:
Taku Nonomura
(Tohoku Univ, Presto, JST)
In the present study, a family of Kalman filter dynamic mode decomposition (KFDMD) for system identification is reviewed and the preliminary results on a new formulation of extended Kalman filter dynamic mode decomposition (EKFDMD) is discussed. First, the advantages and points to be improved for KFDMD are summarized, and the one of the problems is pointed out to be used with batch proper orthogonal decomposition (POD). Because of the problem above, it cannot run as a pure online algorithm. Regarding this problem, EKFDMD is improved to be able to handle a streaming dataset in this study. In the presentation, rough idea is presented and the preliminary results of EKFDMD are summarized.
*This work was partially supported by JST Presto ( Grant Number JPMJPR1678).
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DFD.Q01.11
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