A statistically consistent Koopman identification method for nonlinear systems with inputs and general noise, based on deep state-space encoders and multiple-shooting prediction error minimization.
Mezi ´c, Koopman operator, geometry, and learning of dynamical systems , Notices of the American Mathematical Society, 68 (2021), pp
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Learning Koopman Models From Data Under General Noise Conditions
A statistically consistent Koopman identification method for nonlinear systems with inputs and general noise, based on deep state-space encoders and multiple-shooting prediction error minimization.