PySINDy tutorial 1: overview of PySINDy for sparse system identification

Описание к видео PySINDy tutorial 1: overview of PySINDy for sparse system identification

Automated data-driven modeling, the process of directly discovering the governing equations of a dynamical system from data, is increasingly being used across the scientific community. PySINDy (https://github.com/dynamicslab/pysindy) is a Python package that provides tools for applying the sparse identification of nonlinear dynamics (SINDy) approach to data-driven model discovery. In a recent update to PySINDy (https://arxiv.org/pdf/2111.08481.pdf), we implement several advanced features that enable the discovery of more general differential equations from noisy and limited data. Here we provide a brief overview of the SINDy method, with followup tutorial videos for effectively using the PySINDy code.

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