Convergence Analysis of Asymptotical Regularization and Runge-Kutta Integrators for Linear Inverse Problems under Variational Source Conditions

Yubin Zhao , Peter Mathé , Shuai Lu

CSIAM Trans. Appl. Math. ›› 2020, Vol. 1 ›› Issue (4) : 693 -714.

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CSIAM Trans. Appl. Math. ›› 2020, Vol. 1 ›› Issue (4) : 693 -714. DOI: 10.4208/csiam-am.2020-0022
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Convergence Analysis of Asymptotical Regularization and Runge-Kutta Integrators for Linear Inverse Problems under Variational Source Conditions

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Abstract

Variational source conditions are known to be a versatile tool for establish-ing error bounds, and these recently attract much attention. We establish sufficient conditions for general spectral regularization methods which yield convergence rates under variational source conditions. Specifically, we revisit the asymptotical regular-ization, Runge-Kutta integrators, and verify that these methods satisfy the proposed conditions. Numerical examples confirm the theoretical findings.

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Linear ill-posed problems / regularization theory / variational source conditions / asymptotical regularization / Runge-Kutta integrators

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Yubin Zhao, Peter Mathé, Shuai Lu. Convergence Analysis of Asymptotical Regularization and Runge-Kutta Integrators for Linear Inverse Problems under Variational Source Conditions. CSIAM Trans. Appl. Math., 2020, 1(4): 693-714 DOI:10.4208/csiam-am.2020-0022

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