Long-Time Asymptotics of the Filtering Distribution for Partially Observed Chaotic Dynamical Systems

DOI10.1137/140997336zbMath1337.93094arXiv1411.6510OpenAlexW1721419864MaRDI QIDQ2801321

Daniel Sanz-Alonso, Andrew M. Stuart

Publication date: 6 April 2016

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1411.6510

zbMATH Keywords

chaosdissipative dynamical systemsNavier-Stokes equationfilteringsmall noiseLorenz models

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Dynamical systems in control (37N35)

Related Items (10)

Shadowing-Based Data Assimilation Method for Partially Observed Models ⋮ Projected Shadowing-Based Data Assimilation ⋮ Almost Sure Error Bounds for Data Assimilation in Dissipative Systems with Unbounded Observation Noise ⋮ Performance analysis of local ensemble Kalman filter ⋮ Autodifferentiable Ensemble Kalman Filters ⋮ Rank Deficiency of Kalman Error Covariance Matrices in Linear Time-Varying System With Deterministic Evolution ⋮ Reduced-order autodifferentiable ensemble Kalman filters ⋮ Optimization based methods for partially observed chaotic systems ⋮ On concentration properties of partially observed chaotic systems ⋮ Ergodicity and accuracy of optimal particle filters for Bayesian data assimilation

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