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Asymptotically Stable Data-Driven Koopman Operator Approximation with Inputs using Total Extended DMD
The Koopman operator framework can be used to identify a data-driven model of a nonlinear system. Unfortunately, when the data is corrupted by noise, the identified model can be biased. Additionally, depending on the choice of lifting functions, the identified model can be unstable, even when the un
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