Filtering nonlinear spatio-temporal chaos with autoregressive linear stochastic models
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Publication:446142
DOI10.1016/j.physd.2012.03.003zbMath1300.93168OpenAlexW2165160860WikidataQ57431396 ScholiaQ57431396MaRDI QIDQ446142
Publication date: 28 August 2012
Published in: Physica D (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.physd.2012.03.003
Ornstein-Uhlenbeck processKalman filterautoregressive modelsAR(p) filterLorenz 96 (L-96) modelnon-Markovian linear stochastic model
Inference from stochastic processes and prediction (62M20) Filtering in stochastic control theory (93E11)
Related Items (4)
Forecasting turbulent modes with nonparametric diffusion models: learning from noisy data ⋮ Uncertainty quantification of nonlinear Lagrangian data assimilation using linear stochastic forecast models ⋮ Information quantity evaluation of nonlinear time series processes and applications ⋮ An algebraic method for constructing stable and consistent autoregressive filters
Uses Software
Cites Work
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