System Identification with Copula Entropy
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Abstract (arXiv)
Identifying differential equation governing dynamical system is an important problem with wide applications. Copula Entropy (CE) is a mathematical concept for measuring statistical independence in information theory. In this paper we propose a method for identifying differential equation of dynamical systems with CE. The problem is considered as a variable selection problem and solved with the previously proposed CE-based method for variable selection. The proposed method composed of two components: the difference operator and the CE estimator. Since both components can be done non-parametrically, the proposed method is therefore model-free and hyperparameter-free. The simulation experiment with the 3D Lorenz system verified the effectiveness of the proposed method.
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References · 5
- 2017Machine Learning of Linear Differential Equations using Gaussian Processescited by 139
- 2023Benchmarking sparse system identification with low-dimensional chaoscited by 19
- 2019Estimating Transfer Entropy via Copula Entropycited by 6
- 2019Variable Selection with Copula Entropycited by 5
- 2023Identifying Time Lag in Dynamical Systems with Copula Entropy based Transfer Entropycited by 1
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