Nature Communications (Nov 2018)

Deep learning for universal linear embeddings of nonlinear dynamics

  • Bethany Lusch,
  • J. Nathan Kutz,
  • Steven L. Brunton

DOI
https://doi.org/10.1038/s41467-018-07210-0
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 10

Abstract

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It is often advantageous to transform a strongly nonlinear system into a linear one in order to simplify its analysis for prediction and control. Here the authors combine dynamical systems with deep learning to identify these hard-to-find transformations.