On the Asymptotical Regularization for Linear Inverse Problems in Presence of White Noise
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Publication:5149777
DOI10.1137/20M1330841zbMath1459.65080arXiv2004.04451MaRDI QIDQ5149777
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Publication date: 8 February 2021
Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2004.04451
convergence ratesdata assimilationKalman-Bucy filterstatistical inverse problemsasymptotical regularization
Inference from stochastic processes and prediction (62M20) Linear operators and ill-posed problems, regularization (47A52) Numerical solution to inverse problems in abstract spaces (65J22)
Related Items (5)
Stochastic asymptotical regularization for linear inverse problems ⋮ An asymptotical regularization with convex constraints for inverse problems ⋮ On the asymptotical regularization with convex constraints for nonlinear 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
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