Open AccessA kernel-based method for data-driven koopman spectral analysis
Author(s) -
Matthew O. Williams,
Clarence W. Rowley,
Ioannis G. Kevrekidis
Publication year - 2015
Publication title -
journal of computational dynamics
Language(s) - English
Resource type - Journals
eISSN - 2158-2505
pISSN - 2158-2491
DOI - 10.3934/jcd.2015005
Subject(s) - dynamic mode decomposition , scalar (mathematics) , eigenfunction , observable , kernel (algebra) , mathematics , representer theorem , vorticity , algorithm , subspace topology , scalar field , computer science , kernel embedding of distributions , kernel method , mathematical analysis , artificial intelligence , discrete mathematics , geometry , physics , eigenvalues and eigenvectors , mathematical physics , quantum mechanics , machine learning , vortex , support vector machine , thermodynamics