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Applicable Analysis
An International Journal
Volume 97, 2018 - Issue 15
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Articles

Convergence analysis of simplified iteratively regularized Gauss–Newton method in a Banach space setting

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Pages 2686-2719 | Received 26 Jul 2017, Accepted 26 Sep 2017, Published online: 26 Oct 2017

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Sharad Kumar Dixit. (2023) A Study of an Iteratively-Regularized Simplified Landweber Iteration for Nonlinear Inverse Problems in Hilbert Spaces. Numerical Functional Analysis and Optimization 44:7, pages 619-652.
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Articles from other publishers (7)

Gaurav Mittal. (2024) Nonstationary iterated frozen Tikhonov regularization with uniformly convex penalty terms for solving inverse problems. Applied Mathematics and Computation 468, pages 128519.
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Ruixue Gu, Hongsun Fu & Zhuoyue Wang. (2023) Generalized Inexact Newton-Landweber Iteration for Possibly Non-Smooth Inverse Problems in Banach Spaces. Mathematics 11:7, pages 1706.
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Pallavi Mahale, Ankit Singh & Ankush Kumar. (2022) Error estimates for the simplified iteratively regularized Gauss–Newton method under a general source condition. The Journal of Analysis 31:1, pages 295-328.
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Gaurav Mittal & Ankik Kumar Giri. (2022) Convergence analysis of iteratively regularized Gauss–Newton method with frozen derivative in Banach spaces. Journal of Inverse and Ill-posed Problems 0:0.
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Zhenwu Fu, Yong Chen, Li Li & Bo Han. (2021) Analysis of a generalized regularized Gauss–Newton method under heuristic rule in Banach spaces. Inverse Problems 37:12, pages 125003.
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Anatoly Bakushinsky & Alexandra Smirnova. (2020) A study of frozen iteratively regularized Gauss–Newton algorithm for nonlinear ill-posed problems under generalized normal solvability condition. Journal of Inverse and Ill-posed Problems 28:2, pages 275-286.
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Pallavi Mahale & Sharad Kumar Dixit. (2020) Simplified Iteratively Regularized Gauss–Newton Method in Banach Spaces Under a General Source Condition. Computational Methods in Applied Mathematics 20:2, pages 321-341.
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