Convergence of Levenberg--Marquardt method in Banach spaces

We study the Levenberg--Marquardt method for nonlinear inverse problems in Banach spaces under a Hölder stability estimate. Under suitable assumptions on the geometry of the Banach space and the Fréchet derivative of the measurement operator, we establish the well-definedness of the method, local convergence and convergence rates for exact data, and the monotonic decrease of the Bregman distance up to the stopping index for noisy data. These results extend the corresponding Hilbert space theory to the Banach space setting.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-29
DOI
https://doi.org/10.48550/arxiv.2610.39131
Primary Topic
Numerical methods in inverse problems
Type
preprint
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preprint

Convergence of Levenberg--Marquardt method in Banach spaces

Sei Nagayasu, Akari Ishida
arXiv (Cornell University)
Numerical methods in inverse problems
preprint

Convergence of Levenberg--Marquardt method in Banach spaces

Sei Nagayasu, Akari Ishida
preprint en

Abstract

We study the Levenberg--Marquardt method for nonlinear inverse problems in Banach spaces under a Hölder stability estimate. Under suitable assumptions on the geometry of the Banach space and the Fréchet derivative of the measurement operator, we establish the well-definedness of the method, local convergence and convergence rates for exact data, and the monotonic decrease of the Bregman distance up to the stopping index for noisy data. These results extend the corresponding Hilbert space theory to the Banach space setting.

arXiv (Cornell University)
Numerical methods in inverse problems
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Convergence of Levenberg--Marquardt method in Banach spaces — Sei Nagayasu, Akari Ishida · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS