Quantifying Bayesian filter performance for turbulent dynamical systems through information theory
type: Item
instance of: scholarly article
title: Quantifying Bayesian filter performance for turbulent dynamical systems through information theory
zbMATH Open document ID: 1302.93212
published in: Communications in Mathematical Sciences
publication date: 2014-12-22T00:00:00Z
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 62B10
Mathematics Subject Classification ID: 94A17
Mathematics Subject Classification ID: 60G35
Mathematics Subject Classification ID: 60H10
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 60H30
Mathematics Subject Classification ID: 35C20
Mathematics Subject Classification ID: 76F55
zbMATH DE Number: 6382040
zbMATH Keywords: Kalman filter
zbMATH Keywords: information theory
zbMATH Keywords: uncertainty quantification
zbMATH Keywords: turbulent dynamical systems
author: Michal Branicki
author: Andrew J. Majda
MaRDI profile type: Publication
full work available at URL: cms.2014.v12.n5.a6
OpenAlex ID: W1995003545
DOI: 10.4310/CMS.2014.V12.N5.A6
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description: scientific article; zbMATH DE number 6382040