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Variable projection methods for an optimized dynamic mode decomposition
[article]
2017
arXiv
pre-print
The dynamic mode decomposition (DMD) has become a leading tool for data-driven modeling of dynamical systems, providing a regression framework for fitting linear dynamical models to time-series measurement data. We present a simple algorithm for computing an optimized version of the DMD for data which may be collected at unevenly spaced sample times. By making use of the variable projection method for nonlinear least squares problems, the algorithm is capable of solving the underlying nonlinear
arXiv:1704.02343v1
fatcat:lhlkp3xd5zhxbpon46thaap3pq