System Identification with Copula Entropy
This work addresses system identification for dynamical systems, but it appears incremental as it applies an existing Copula Entropy-based variable selection method to this domain.
The authors tackled the problem of identifying differential equations governing dynamical systems by proposing a method based on Copula Entropy, which is model-free and hyperparameter-free, and verified its effectiveness through simulation experiments on the 3D Lorenz system.
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.