Improvements on Extended Kalman Filter Dynamic Mode Decomposition for Noisy Dataset

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.