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Iteratively Regularized Gauss–Newton Method for Nonlinear Inverse Problems with Random Noise
Work
Year: 2009
Type: article
Abstract: We study the convergence of regularized Newton methods applied to nonlinear operator equations in Hilbert spaces if the data are perturbed by random noise. It is shown that the expected square error i... more
Cites: 27
Cited by: 70
Related to: 10
FWCI: 4.837
Citation percentile (by year/subfield): 97.28
Sustainable Development Goal Reduced inequalities
Open Access status: green