How entropic regression beats the outliers problem in nonlinear system identification-Reference-Cited by-同舟云学术

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How entropic regression beats the outliers problem in nonlinear system identification

Published:2020-01 Issue:1 Volume:30 Page:013107
ISSN:1054-1500
Container-title:Chaos: An Interdisciplinary Journal of Nonlinear Science
language:en
Short-container-title:Chaos

Author:

AlMomani Abd AlRahman R.¹²^ORCID,Sun Jie³^ORCID,Bollt Erik¹²^ORCID

Affiliation:

1. Electrical and Computer Engineering, Clarkson University, Potsdam, New York 13699, USA

2. Clarkson Center for Complex Systems Science (C3S2), Potsdam, New York 13699, USA

3. Theory Lab, Hong Kong Research Centre of Huawei Tech, Hong Kong 852, China

Funder

Defense Advanced Research Projects Agency

Office of Naval Research

Simons Foundation

Army Research Office

Publisher

AIP Publishing

Subject

Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

Link

http://aip.scitation.org/doi/am-pdf/10.1063/1.5133386

Reference36 articles.

1. Discovering governing equations from data by sparse identification of nonlinear dynamical systems

2. Modeling and nonlinear parameter estimation with Kronecker product representation for coupled oscillators and spatiotemporal systems

3. Orthogonal least squares methods and their application to non-linear system identification

4. Adaptive algorithms for sparse system identification

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