Data-Driven Computational Methods
Parameter and Operator Estimations
Modern scientific computational methods are undergoing a transformative change; big data and statistical learning methods now have the potential to outperform the classical first-principles modeling paradigm. This book bridges this transition, connecting the theory of probability, stochastic processes, functional analysis, numerical analysis, and differential geometry. It describes two classes of computational methods to leverage data for modeling dynamical systems. The first is concerned with data fitting algorithms to estimate parameters in parametric models that are postulated on the basis of physical or dynamical laws. The second is on op…
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Produktdetails
- ISBN: 978-1-108-61513-6
- EAN: 9781108615136
- Produktnummer: 27737263
- Verlag: Cambridge University Press
- Sprache: Englisch
- Erscheinungsjahr: 2018
- Seitenangabe: 0 S.
- Plattform: PDF
- Masse: 6'756 KB
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