Approximation error approach in spatiotemporally chaotic models with application to Kuramoto-Sivashinsky equation
type: Item
instance of: scholarly article
title: Approximation error approach in spatiotemporally chaotic models with application to Kuramoto-Sivashinsky equation
zbMATH Open document ID: 1469.62084
author: Heikki Haario
author: Janne M. J. Huttunen
author: Jari P. Kaipio
published in: Computational Statistics and Data Analysis
publication date: 2018-08-20T00:00:00Z
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62M20
zbMATH DE Number: 6920679
zbMATH Keywords: nonstationary inverse problems
zbMATH Keywords: state estimation
zbMATH Keywords: filtering
zbMATH Keywords: spatiotemporal chaos
zbMATH Keywords: chaotic models
zbMATH Keywords: Bayesian approximation error approach
describes a project that uses: Matlab
describes a project that uses: ode23s
describes a project that uses: dlm
describes a project that uses: ode23
describes a project that uses: ode45
describes a project that uses: Ode15s
describes a project that uses: ode113
describes a project that uses: MATLAB ODE suite
MaRDI profile type: Publication
full work available at URL: j.csda.2018.01.015
OpenAlex ID: W2790667592
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DOI: 10.1016/J.CSDA.2018.01.015
description: scientific article; zbMATH DE number 6920679