The Occupation Kernel Method for Nonlinear System Identification-Reference-Cited by-同舟云学术

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The Occupation Kernel Method for Nonlinear System Identification

Published:2024-06-11 Issue:3 Volume:62 Page:1643-1668
ISSN:0363-0129
Container-title:SIAM Journal on Control and Optimization
language:en
Short-container-title:SIAM J. Control Optim.

Author:

Rosenfeld Joel A.¹^ORCID,Russo Benjamin P.²^ORCID,Kamalapurkar Rushikesh³^ORCID,Johnson Taylor T.⁴^ORCID

Affiliation:

1. Department of Mathematics and Statistics, University of South Florida, Tampa, FL 33620 USA.

2. Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 USA.

3. Department of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK 74078 USA.

4. Institute for Software Integrated Systems, Department of Computer Science, Vanderbilt University, Nashville, TN 37212 USA.

Funder

Air Force Office of Scientific Research

Office of Naval Research

Air Force Research Laboratory

Defense Advanced Research Projects Agency

National Science Foundation

Department of Energy

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference42 articles.

1. Nonlinear System Identification

2. Regularized nonparametric Volterra kernel estimation

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

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