On a heuristic stopping rule for the regularization of inverse problems by the augmented Lagrangian method

Qinian Jin*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    18 Citations (Scopus)

    Abstract

    In this paper we propose a heuristic stopping rule of Hanke–Raus type for the regularization of linear ill-posed inverse problems by the augmented Lagrangian method. This stopping rule requires no information on the noise level. Under certain source conditions, we derive a posteriori error estimates in term of Bregman distance. By imposing certain conditions on the noise data, we establish convergence results. Numerical results are presented to illustrate the performance.

    Original languageEnglish
    Pages (from-to)973-992
    Number of pages20
    JournalNumerische Mathematik
    Volume136
    Issue number4
    DOIs
    Publication statusPublished - 1 Aug 2017

    Fingerprint

    Dive into the research topics of 'On a heuristic stopping rule for the regularization of inverse problems by the augmented Lagrangian method'. Together they form a unique fingerprint.

    Cite this