1 code implementation • 21 Sep 2016 • Samuel H. Rudy, Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz
We propose a sparse regression method capable of discovering the governing partial differential equation(s) of a given system by time series measurements in the spatial domain.
Pattern Formation and Solitons
2 code implementations • 11 Sep 2015 • Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz
In this work, we combine sparsity-promoting techniques and machine learning with nonlinear dynamical systems to discover governing physical equations from measurement data.
Dynamical Systems
2 code implementations • 22 Sep 2014 • Joshua L. Proctor, Steven L. Brunton, J. Nathan Kutz
We develop a new method which extends Dynamic Mode Decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, complex systems.
Optimization and Control
