Nonlinear System Identification: Learning While Respecting Physical Models Using a Sequential Monte Carlo Method-Reference-Cited by-同舟云学术

Nonlinear System Identification: Learning While Respecting Physical Models Using a Sequential Monte Carlo Method

Published:2022-02 Issue:1 Volume:42 Page:75-102
ISSN:1066-033X
Container-title:IEEE Control Systems
language:
Short-container-title:IEEE Control Syst.

Author:

Wigren Anna¹,Wagberg Johan¹,Lindsten Fredrik²,Wills Adrian G.³,Schon Thomas B.⁴

Affiliation:

1. Uppsala University, Uppsala, Sweden

2. Department of Computer and Information Science, Linköping University, Linköping, Sweden

3. University of Newcastle, School of Engineering, Callaghan, Australia

4. Department of Information Technology, Uppsala University, Uppsala, Sweden

Funder

Knut and Alice Wallenberg Foundation

Swedish Foundation for Strategic Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Modeling and Simulation,Control and Systems Engineering,Electrical and Electronic Engineering,Modeling and Simulation,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/5488303/9682614/09682628.pdf?arnumber=9682628

Reference111 articles.

1. A Stochastic Approximation Method

2. Particle Approximations of the Score and Observed Information Matrix for Parameter Estimation in State–Space Models With Linear Computational Cost

3. Inference in Hidden Markov Models

4. Bayesian Filtering and Smoothing

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