Iterative Sparse Identification of Nonlinear Dynamics

In order to extract governing equations from time-series data, various approaches are proposed. Among those, sparse identification of nonlinear dynamics (SINDy) stands out as a successful method capable of modeling governing equations with a minimal number of terms, utilizing the principles of compr...

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Bibliographic Details
Main Author: Jinho Choi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of Signal Processing
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10750024/
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