Expectation maximization based sparse identification of cyberphysical system

DOI10.1002/rnc.5325zbMath1526.93031OpenAlexW3101162893MaRDI QIDQ6089856

Yunlong Dong, Unnamed Author

Publication date: 13 November 2023

Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/rnc.5325

zbMATH Keywords

system identificationexpectation maximizationcyberphysical systems

Mathematics Subject Classification ID

System identification (93B30) Control/observation systems involving computers (process control, etc.) (93C83) Networked control (93B70)

Related Items (1)

A novel recursive approach for online identification of continuous‐time switched nonlinear systems

Cites Work

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• Discovering governing equations from data by sparse identification of nonlinear dynamical systems
• A new kernel-based approach to hybrid system identification
• Identification of switched linear systems via sparse optimization
• On the convergence properties of the EM algorithm
• Identification of piecewise affine systems via mixed-integer programming.
• Estimating the probability of success of a simple algorithm for switched linear regression
• Identification of hybrid systems. A tutorial
• Identification of piecewise affine systems based on statistical clustering technique
• Identification and frequency domain analysis of non-stationary and nonlinear systems using time-varying NARMAX models
• A Sparse Bayesian Approach to the Identification of Nonlinear State-Space Systems
• Automated reverse engineering of nonlinear dynamical systems
• The Bayesian Lasso
• A Bayesian approach to identification of hybrid systems
• A bounded-error approach to piecewise affine system identification
• Compressed sensing

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