On inertial Levenberg-Marquardt type methods for solving nonlinear ill-posed operator equations

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Hauptverfasser: Leitão, Antonio, Rabelo, Joel C., Lorenz, Dirk A., Winkler, Maximilian
Format: Preprint
Veröffentlicht: 2024
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author Leitão, Antonio
Rabelo, Joel C.
Lorenz, Dirk A.
Winkler, Maximilian
author_facet Leitão, Antonio
Rabelo, Joel C.
Lorenz, Dirk A.
Winkler, Maximilian
contents In these notes we propose and analyze an inertial type method for obtaining stable approximate solutions to nonlinear ill-posed operator equations. The method is based on the Levenberg-Marquardt (LM) iteration. The main obtained results are: monotonicity and convergence for exact data, stability and semi-convergence for noisy data. Regarding numerical experiments we consider: i) a parameter identification problem in elliptic PDEs, ii) a parameter identification problem in machine learning; the computational efficiency of the proposed method is compared with canonical implementations of the LM method.
format Preprint
id arxiv_https___arxiv_org_abs_2406_07044
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On inertial Levenberg-Marquardt type methods for solving nonlinear ill-posed operator equations
Leitão, Antonio
Rabelo, Joel C.
Lorenz, Dirk A.
Winkler, Maximilian
Numerical Analysis
65J20, 47J06
In these notes we propose and analyze an inertial type method for obtaining stable approximate solutions to nonlinear ill-posed operator equations. The method is based on the Levenberg-Marquardt (LM) iteration. The main obtained results are: monotonicity and convergence for exact data, stability and semi-convergence for noisy data. Regarding numerical experiments we consider: i) a parameter identification problem in elliptic PDEs, ii) a parameter identification problem in machine learning; the computational efficiency of the proposed method is compared with canonical implementations of the LM method.
title On inertial Levenberg-Marquardt type methods for solving nonlinear ill-posed operator equations
topic Numerical Analysis
65J20, 47J06
url https://arxiv.org/abs/2406.07044