Dynamic mode decomposition using a Kalman filter for parameter estimation

@article{Nonomura2018DynamicMD,
  title={Dynamic mode decomposition using a Kalman filter for parameter estimation},
  author={Taku Nonomura and Hisaichi Shibata and Ryoji Takaki},
  journal={AIP Advances},
  year={2018}
}
A novel dynamic mode decomposition (DMD) method based on a Kalman filter is proposed. This paper explains the fast algorithm of the proposed Kalman filter DMD (KFDMD) in combination with truncated proper orthogonal decomposition for many-degree-of-freedom problems. Numerical experiments reveal that KFDMD can estimate eigenmodes more precisely compared with standard DMD or total least-squares DMD (tlsDMD) methods for the severe noise condition if the nature of the observation noise is known… 

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