Convergence analysis of iteratively regularized Landweber iteration with uniformly convex constraints in Banach spaces

被引:0
|
作者
Mittal, Gaurav [1 ]
Bajpai, Harshit [2 ]
Giri, Ankik Kumar [2 ]
机构
[1] Def Res & Dev Org, Near Metcalfe House, New Delhi 110054, India
[2] Indian Inst Technol Roorkee, Dept Math, Roorkee 247667, Uttarakhand, India
关键词
Inverse problems; Ill-posed operator equations; Regularization; LIPSCHITZ STABILITY;
D O I
10.1016/j.jco.2024.101897
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In Banach spaces, the convergence analysis of iteratively regularized Landweber iteration (IRLI) is recently studied via conditional stability estimates. But the formulation of IRLI does not include general non-smooth convex penalty functionals, which is essential to capture special characteristics of the sought solution. In this paper, we formulate a generalized form of IRLI so that its formulation includes general non-smooth uniformly convex penalty functionals. We study the convergence analysis and derive the convergence rates of the generalized method solely via conditional stability estimates in Banach spaces for both the perturbed and unperturbed data. We also discuss few examples of inverse problems on which our method is applicable. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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页数:17
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