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Proceedings of the National Academy of Sciences· 2016Q1

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

Steven L. Brunton, Joshua L. Proctor, J. Nathan Kutz

Short summary

A new algorithm uses sparsity-promoting techniques and machine learning to discover governing equations from noisy data, creating parsimonious models that balance accuracy and complexity.

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Field: Statistical and Nonlinear Physics

Statistical and Nonlinear PhysicsPhysics and Astronomy