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We derive a data-driven method for the approximation of the Koopman generator called gEDMD, which can be regarded as a straightforward extension of EDMD (extended dynamic mode decomposition).
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On dynamic mode decomposition: Theory and applications
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Linear identification of nonlinear systems: A lifting technique based on the Koopman operator
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