Coercivity-based analysis and its application to an inverse source problem for a subdiffusion equation with time-dependent principal parts

Abstract In this article, we investigate an inverse source problem for subdiffusion equations with time-dependent principal parts using distributed observations. We analyze coercivity properties of fractional derivatives. As applications, we use a coercivity property to establish a Lipschitz stability estimate for an inverse problem of determining the temporal component in the source term, which is a new result to the best knowledge of the authors. Numerically, we transform the inverse source problem into an optimization framework, incorporating Tikhonov regularization to mitigate the ill-posedness of the inverse problem. We then propose an iterative thresholding algorithm to solve this optimization problem efficiently. Finally, we present several numerical experiments to validate the accuracy and the efficiency of our proposed algorithm.

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Publication Details

Journal
Inverse Problems
Published
2024-11-26
DOI
https://doi.org/10.1088/1361-6420/ad9775
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
0.00

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article

Coercivity-based analysis and its application to an inverse source problem for a subdiffusion equation with time-dependent principal parts

Masahiro Yamamoto, Zhiyuan Li, Daijun Jiang
Inverse Problems
Numerical methods in inverse problems
article

Coercivity-based analysis and its application to an inverse source problem for a subdiffusion equation with time-dependent principal parts

Masahiro Yamamoto, Zhiyuan Li, Daijun Jiang
article en

Abstract

Abstract In this article, we investigate an inverse source problem for subdiffusion equations with time-dependent principal parts using distributed observations. We analyze coercivity properties of fractional derivatives. As applications, we use a coercivity property to establish a Lipschitz stability estimate for an inverse problem of determining the temporal component in the source term, which is a new result to the best knowledge of the authors. Numerically, we transform the inverse source problem into an optimization framework, incorporating Tikhonov regularization to mitigate the ill-posedness of the inverse problem. We then propose an iterative thresholding algorithm to solve this optimization problem efficiently. Finally, we present several numerical experiments to validate the accuracy and the efficiency of our proposed algorithm.

Inverse ProblemsVol. 40(12)
Ningbo University (CN), Ningbo University of Technology (CN), Central China Normal University (CN), The University of Tokyo (JP)
National Natural Science Foundation of China, Japan Society for the Promotion of Science
Openalex Percentile: Top 64%
Numerical methods in inverse problems
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