Convergence analysis of a two-point gradient method for nonlinear ill-posed problems

被引：47
|
作者：
Hubmer, Simon [1 ]
Ramlau, Ronny [2 ,3 ]
机构：
[1] Johannes Kepler Univ Linz, Doctoral Program Computat Math, Altenbergerstr 69, A-4040 Linz, Austria
[2] Johannes Kepler Univ Linz, Inst Ind Math, Altenbergerstr 69, A-4040 Linz, Austria
[3] Johann Radon Inst Linz, Altenbergerstr 69, A-4040 Linz, Austria
来源：
INVERSE PROBLEMS | 2017年 / 33卷 / 09期
基金：
奥地利科学基金会;
关键词：
two-point gradient method; Nesterov acceleration scheme; Landweber iteration; steepest descent; minimal error; regularization method; SPECT; LANDWEBER ITERATION; ALGORITHM;
D O I：
10.1088/1361-6420/aa7ac7
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We perform a convergence analysis of a two-point gradient method which is based on Landweber iteration and on Nesterov's acceleration scheme. Additionally, we show the usefulness of this method via two numerical example problems based on a nonlinear Hammerstein operator and on the nonlinear inverse problem of single photon emission computed tomography.
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页数：30
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