Filter based methods for statistical linear inverse problems

DOI10.4310/CMS.2017.v15.n7.a4zbMath1383.93086arXiv1512.01955MaRDI QIDQ1709634

Marco A. Iglesias, Andrew M. Stuart, Kui Lin, Shuai Lu

Publication date: 6 April 2018

Published in: Communications in Mathematical Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1512.01955

zbMATH Keywords

Kalman filterstatistical inverse problems3D-VARartificial dynamics

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10) Linear operators and ill-posed problems, regularization (47A52) Inverse problems in optimal control (49N45) Numerical solution to inverse problems in abstract spaces (65J22)

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On an iterative fractional Tikhonov-Landweber method for ill-posed problems ⋮ Iterate averaging, the Kalman filter, and 3DVAR for linear inverse problems ⋮ On a Dynamic Variant of the Iteratively Regularized Gauss–Newton Method with Sequential Data ⋮ On the Asymptotical Regularization for Linear Inverse Problems in Presence of White Noise ⋮ Weak-norm posterior contraction rate of the 4DVAR method for linear severely ill-posed problems ⋮ Identify the fractional order and diffusion coefficient in a fractional diffusion wave equation ⋮ Iterative ensemble Kalman methods: a unified perspective with some new variants

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