Summary
International Symposium on Nonlinear Theory and Its Applications
2022
Session Number:D1L-D
Session:
Number:D1L-D-01
On Analytical Construction of Observable Functions in Extended Dynamic Mode Decomposition for Nonlinear Estimation and Prediction
Marcos Netto , Yoshihiko Susuki , Venkat Krishnan , Yingchen Zhang,
pp.621-621
Publication Date:12/12/2022
Online ISSN:2188-5079
Summary:
We propose an analytical construction of observable functions in the extended dynamic mode decomposition (EDMD) algorithm. EDMD is a numerical method for approximating the spectral properties of the Koopman operator. The choice of observable functions is fundamental for the application of EDMD to nonlinear problems arising in systems and control.