PySINDy: A comprehensive Python package for robust sparse system identification-Reference-Cited by-同舟云学术

PySINDy: A comprehensive Python package for robust sparse system identification

Published:2022-01-29 Issue:69 Volume:7 Page:3994
ISSN:2475-9066
Container-title:Journal of Open Source Software
language:
Short-container-title:JOSS

Author:

Kaptanoglu Alan,de Silva Brian,Fasel Urban,Kaheman Kadierdan,Goldschmidt Andy,Callaham Jared,Delahunt Charles,Nicolaou Zachary,Champion Kathleen,Loiseau Jean-Christophe,Kutz J.,Brunton Steven

Publisher

The Open Journal

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://joss.theoj.org/papers/10.21105/joss.03994.pdf

Reference38 articles.

1. Numerical differentiation of experimental data: local versus global methods

2. Numerical Differentiation of Noisy, Nonsmooth Data

3. The solution path of the generalized lasso

4. A toolkit for data-driven discovery of governing equations in high-noise regimes, Delahunt, Charles B and Kutz, J Nathan, arXiv preprint arXiv:2111.04870, 2021

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

Cited by 73 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning macroscopic equations of motion from dissipative particle dynamics simulations of fluids;Computer Methods in Applied Mechanics and Engineering;2024-12

2. EKF–SINDy: Empowering the extended Kalman filter with sparse identification of nonlinear dynamics;Computer Methods in Applied Mechanics and Engineering;2024-11

3. TendrilBot: Modular soft robot with versatile radial grasping and locomotion capabilities;Sensors and Actuators A: Physical;2024-11

4. Bayesian Physics-informed Neural Networks for system identification of inverter-dominated power systems;Electric Power Systems Research;2024-10

5. Physics-informed genetic programming for discovery of partial differential equations from scarce and noisy data;Journal of Computational Physics;2024-10