Probabilistic inference for dynamical systems
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Archivos
Fecha
2018-09
Autores
Profesor/a Guía
Facultad/escuela
Idioma
en
Título de la revista
ISSN de la revista
Título del volumen
Editor
MDPI AG
Nombre de Curso
Licencia CC
Licencia CC
Resumen
A general framework for inference in dynamical systems is described, based on the language of Bayesian probability theory and making use of the maximum entropy principle. Taking the concept of a path as fundamental, the continuity equation and Cauchy's equation for fluid dynamics arise naturally, while the specific information about the system can be included using the maximum caliber (or maximum path entropy) principle. © 2018 by the authors.
Notas
Indexación: Scopus.
Palabras clave
Bayesian inference, Dynamical systems, Fluid equations
Citación
Entropy, 20(9), art. no. 696.