A convergence analysis of the iteratively regularized Gauss-Newton method under the Lipschitz condition

Qinian Jin

doi:10.1088/0266-5611/24/4/045002

A convergence analysis of the iteratively regularized Gauss-Newton method under the Lipschitz condition

Qinian Jin^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

32 Citations (Scopus)

Abstract

In this paper we consider the iteratively regularized Gauss-Newton method for solving nonlinear ill-posed inverse problems. Under merely the Lipschitz condition, we prove that this method together with an a posteriori stopping rule defines an order optimal regularization method if the solution is regular in some suitable sense.

Original language	English
Article number	045002
Journal	Inverse Problems
Volume	24
Issue number	4
DOIs	https://doi.org/10.1088/0266-5611/24/4/045002
Publication status	Published - 1 Aug 2008
Externally published	Yes

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abstract = "In this paper we consider the iteratively regularized Gauss-Newton method for solving nonlinear ill-posed inverse problems. Under merely the Lipschitz condition, we prove that this method together with an a posteriori stopping rule defines an order optimal regularization method if the solution is regular in some suitable sense.",

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AB - In this paper we consider the iteratively regularized Gauss-Newton method for solving nonlinear ill-posed inverse problems. Under merely the Lipschitz condition, we prove that this method together with an a posteriori stopping rule defines an order optimal regularization method if the solution is regular in some suitable sense.

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A convergence analysis of the iteratively regularized Gauss-Newton method under the Lipschitz condition

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