Nesterov acceleration‐based iterative method for backward problem of distributed‐order time‐fractional diffusion equation

This paper is concerned with the inverse problem of determining the initial value of the distributed‐order time‐fractional diffusion equation from the final time observation data, which arises in some ultra‐slow diffusion phenomena in applied areas. Since the problem is ill‐posed, we propose an iterated regularization method based on the Nesterov acceleration strategy to deal with it. Convergence rates for the regularized approximation solution are given under both the a priori and a posteriori regularization parameter choice rules. It is shown that the proposed method can always yield the order optimal convergence rates as long as the iteration parameter which appears in the Nesterov acceleration strategy is chosen large enough. In numerical aspect, the main advantage of the proposed method lies in its simplicity. Specifically, due to the Nesterov acceleration strategy, only a few number of iteration steps are required to obtain the approximation solution, and at each iteration step, we only need to numerically solve the standard initial‐boundary value problem for the distributed‐order time‐fractional diffusion equation. Some numerical examples including one‐dimensional and two‐dimensional cases are presented to illustrate the validity and effectiveness of the proposed method.

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Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2024-08-26
DOI
https://doi.org/10.1002/mma.10415
Citations
1
Primary Topic
Fractional Differential Equations Solutions
Type
article
Field-Weighted Citation Impact
0.40

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article

Nesterov acceleration‐based iterative method for backward problem of distributed‐order time‐fractional diffusion equation

Yuan‐Xiang Zhang, Z.Q. Zhang, Shimin Guo
1 citations
Mathematical Methods in the Applied Sciences
Fractional Differential Equations Solutions
0.40
article

Nesterov acceleration‐based iterative method for backward problem of distributed‐order time‐fractional diffusion equation

Yuan‐Xiang Zhang, Z.Q. Zhang, Shimin Guo
article en
1 citations

Abstract

This paper is concerned with the inverse problem of determining the initial value of the distributed‐order time‐fractional diffusion equation from the final time observation data, which arises in some ultra‐slow diffusion phenomena in applied areas. Since the problem is ill‐posed, we propose an iterated regularization method based on the Nesterov acceleration strategy to deal with it. Convergence rates for the regularized approximation solution are given under both the a priori and a posteriori regularization parameter choice rules. It is shown that the proposed method can always yield the order optimal convergence rates as long as the iteration parameter which appears in the Nesterov acceleration strategy is chosen large enough. In numerical aspect, the main advantage of the proposed method lies in its simplicity. Specifically, due to the Nesterov acceleration strategy, only a few number of iteration steps are required to obtain the approximation solution, and at each iteration step, we only need to numerically solve the standard initial‐boundary value problem for the distributed‐order time‐fractional diffusion equation. Some numerical examples including one‐dimensional and two‐dimensional cases are presented to illustrate the validity and effectiveness of the proposed method.

Mathematical Methods in the Applied SciencesVol. 48(2)
Lanzhou University of Finance and Economics (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Gansu Province, Natural Science Foundation of Shaanxi Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 42%
Fractional Differential Equations Solutions
0.40
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Nesterov acceleration‐based iterative method for backward problem of distributed‐order time‐fractional diffusion equation — Yuan‐Xiang Zhang, Z.Q. Zhang, et al. · Mathematical Methods in the Applied Sciences (2024) | TGRS Research Map | TGRS