# Reconstruction of Ordinary Differential Equations From Time Series Data

@article{Mai2016ReconstructionOO, title={Reconstruction of Ordinary Differential Equations From Time Series Data}, author={Manuel Mai and Mark D. Shattuck and Corey S. O’Hern}, journal={arXiv: Data Analysis, Statistics and Probability}, year={2016} }

We develop a numerical method to reconstruct systems of ordinary differential equations (ODEs) from time series data without {\it a priori} knowledge of the underlying ODEs using sparse basis learning and sparse function reconstruction. We show that employing sparse representations provides more accurate ODE reconstruction compared to least-squares reconstruction techniques for a given amount of time series data. We test and validate the ODE reconstruction method on known 1D, 2D, and 3D systems…

## 4 Citations

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