Inexact Newton regularization combined with two-point gradient methods for nonlinear ill-posed problems *

Author:

Fan BinORCID,Xu ChuanjuORCID

Abstract

Abstract In this paper, we propose an inexact Newton regularization combined with two-point gradient methods for nonlinear ill-posed problems. The basic idea of the proposed method is to linearize the equation around each outer iteration and subsequently apply a so-called two-point gradient method in the inner loop to accelerate the iterative process. Under suitable assumptions, we show that the iteration sequence generated by the proposed algorithm converges to a solution of the related problem in the noiseless situation. Furthermore, the stability and regularization properties of the proposed algorithm are analyzed in the noise-data case. Several numerical examples are provided to validate the theoretical results and to demonstrate the efficiency of the proposed method.

Funder

NSFC

NSFC/ANR joint program

Publisher

IOP Publishing

Subject

Applied Mathematics,Computer Science Applications,Mathematical Physics,Signal Processing,Theoretical Computer Science

Reference34 articles.

1. Deconvolution of appearance potential spectra;Baumeister;Direct Inverse Boundary Value Problems,1991

2. Modern regularization methods for inverse problems;Benning;Acta Numer.,2018

3. On convergence rates for the iteratively regularized Gauss-Newton method;Blaschke;IMA J. Numer. Anal.,1997

4. About a deficit in low-order convergence rates on the example of autoconvolution;Bürger;Appl. Anal.,2015

5. Stability for parameter estimation in two point boundary value problems;Colonius;J. Reine Angew. Math.,1986

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