• Corpus ID: 117800422

Compressive sampling and dynamic mode decomposition

  title={Compressive sampling and dynamic mode decomposition},
  author={Steven L. Brunton and Joshua L. Proctor and J. Nathan Kutz},
  journal={arXiv: Dynamical Systems},
This work develops compressive sampling strategies for computing the dynamic mode decomposition (DMD) from heavily subsampled or output-projected data. The resulting DMD eigenvalues are equal to DMD eigenvalues from the full-state data. It is then possible to reconstruct full-state DMD eigenvectors using $\ell_1$-minimization or greedy algorithms. If full-state snapshots are available, it may be computationally beneficial to compress the data, compute a compressed DMD, and then reconstruct full… 
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