Mathematical strategies for filtering complex systems: Regularly spaced sparse observations

DOI10.1016/j.jcp.2008.01.049zbMath1388.76204OpenAlexW2109153769MaRDI QIDQ924523

Andrew J. Majda, John Harlim

Publication date: 16 May 2008

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2008.01.049

zbMATH Keywords

turbulenceKalman filterfinite differencedata assimilation

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Finite difference methods applied to problems in fluid mechanics (76M20)

Related Items (9)

Dynamic Stochastic Superresolution of sparsely observed turbulent systems ⋮ Numerical strategies for filtering partially observed stiff stochastic differential equations ⋮ Filtering skill for turbulent signals for a suite of nonlinear and linear extended Kalman filters ⋮ Filtering a statistically exactly solvable test model for turbulent tracers from partial observations ⋮ Filtering nonlinear spatio-temporal chaos with autoregressive linear stochastic models ⋮ Mathematical test criteria for filtering complex systems: Plentiful observations ⋮ Ensemble Kalman filters for dynamical systems with unresolved turbulence ⋮ Test models for improving filtering with model errors through stochastic parameter estimation ⋮ Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation

Cites Work

• Statistical and computational inverse problems.
• Quantifying predictability through information theory: small sample estimation in a non-Gaussian framework
• Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter
• Mathematical test criteria for filtering complex systems: Plentiful observations
• Spectral Methods for Time-Dependent Problems
• Explicit off-line criteria for stable accurate time filtering of strongly unstable spatially extended systems
• Stable time filtering of strongly unstable spatially extended systems
• Filtering nonlinear dynamical systems with linear stochastic models
• Observability of Discretized Partial Differential Equations
• The Fourier Method for Nonsmooth Initial Data
• Dimensional reduction for a Bayesian filter
• Information Theory and Stochastics for Multiscale Nonlinear Systems
• Handbook of stochastic methods for physics, chemistry and natural sciences.
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