Work

A simplified L-curve method as error estimator

Year: 2020

Type: article

Abstract: The L-curve method is a well known heuristic method for choosing the regularization parameter for ill-posed problems by selecting it according to the maximal curvature of the L-curve. In this article, we propose a simplified version that replaces the curvature essentially by the derivative of the parameterization on the y-axis. This method shows a similar behaviour to the original L-curve method, but unlike the latter, it may serve as an error estimator under typical conditions. Thus, we can accordingly prove convergence for the simplified L-curve method.

Source: ETNA - Electronic Transactions on Numerical Analysis

DOI: 10.1553/etna_vol53s217

Authors: Stefan Kindermann, Kemal Raik

Institution: Johannes Kepler University of Linz

Language: English

Topic: Numerical methods in inverse problems

Subfield: Mathematical Physics

Field: Mathematics

Domain: Physical Sciences

Open Access status: bronze

Funder: Austrian Science Fund

Award: Nonlinear heuristic regularization for astronomical imaging