Observables and DMD theory
Discovering governing equations from data by sparse identification of nonlinear dynamical systems
This video highlights the recent innovation of using overcomplete libraries and sparse regression to discover nonlinear dynamical systems from time series data.
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- S. Brunton, J. Proctor and J. N. Kutz, Discovering governing equations from data by sparse identification of nonlinear dynamical systems, Proceedings of the National Academy of Sciences (2016).
Data-driven methods for discovery of observables and Koopman embeddings in dynamical systems
This video highlights a presentation at the IPAM workshop on Collective Variables in Classical Mechanics (Workshop II from October 24-28, 2016).
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- Primary collaborators Steven Brunton and Joshua Proctor