Affiliation:
1. Institute for Mathematics University of Potsdam Potsdam Germany
2. Faculty of Mathematics and Physics Charles University Prague Czech Republic
Abstract
AbstractWe discuss discrete‐time dynamical systems depending on a parameter μ. Assuming that the system matrix is given, but the parameter μ is unknown, we infer the most‐likely parameter from an observed trajectory x of the dynamical system. We use parametric eigenpairs of the system matrix computed with Newton's method based on a Chebyshev expansion. We then represent x in the eigenvector basis defined by the and compare the decay of the components with predictions based on the . The resulting estimates for μ are combined using a kernel density estimator to find the most likely value for and a corresponding uncertainty quantification.
Funder
Deutsche Forschungsgemeinschaft
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics
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