Open Source Codes and Algorithms
MATLAB: Dynamic Mode Decomposition code base [Download]
Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems
Videos, lectures notes and code base for this 2016 SIAM book can be found here.
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- J. Nathan Kutz, S. Brunton, B. Brunton and J. Proctor, Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, SIAM (2016).
MATLAB: SINDy code base [Download ZIP file]
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).
PYTHON: PDE-FIND code base [Download]
Data-driven discovery of partial differential equations
This video highlights extensions of our sparse identification for nonlinear dynamical systems (SINDy) to partial differential equations.
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- S. Rudy, J. L. Proctor, S. L. Brunton, and J. N. Kutz Data-driven discovery of partial differential equations, arxiv (2016)
MATLAB: FAS Diagnostics Toolbox [Download]
Computational Neurology: Computational Toolbox for FAS Diagnostics
This video highlights the use of a computational toolbox for evaluating FAS injuries to axons. A MATLAB toolbox is developed that can be used for evaluation.
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