{"title":"Conditional stability and regularization method for inverse source for distributed order time-fractional diffusion equation","authors":"Yongbo Chen, Hao Cheng","doi":"10.1007/s40314-024-02924-y","DOIUrl":null,"url":null,"abstract":"<p>This article is concerned with the problem of source identification for a distributed-order time-fractional diffusion equation (DTFDE). The uniqueness, ill-posedness and conditional stability estimate for the inverse source problem are demonstrated. Our main objective is to reconstruct the stable source term utilizing an iterative generalized quasi-reversibility method(IGQRM). In theory, an a priori and an a posteriori regularization parameter selection strategies are proposed to obtain the convergence estimates between the regularized solution and the exact solution. In numerical experiment, some numerical examples are presented to describe the stability and validity of our proposed regularization method.</p>","PeriodicalId":51278,"journal":{"name":"Computational and Applied Mathematics","volume":"12 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and Applied Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40314-024-02924-y","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article is concerned with the problem of source identification for a distributed-order time-fractional diffusion equation (DTFDE). The uniqueness, ill-posedness and conditional stability estimate for the inverse source problem are demonstrated. Our main objective is to reconstruct the stable source term utilizing an iterative generalized quasi-reversibility method(IGQRM). In theory, an a priori and an a posteriori regularization parameter selection strategies are proposed to obtain the convergence estimates between the regularized solution and the exact solution. In numerical experiment, some numerical examples are presented to describe the stability and validity of our proposed regularization method.
期刊介绍:
Computational & Applied Mathematics began to be published in 1981. This journal was conceived as the main scientific publication of SBMAC (Brazilian Society of Computational and Applied Mathematics).
The objective of the journal is the publication of original research in Applied and Computational Mathematics, with interfaces in Physics, Engineering, Chemistry, Biology, Operations Research, Statistics, Social Sciences and Economy. The journal has the usual quality standards of scientific international journals and we aim high level of contributions in terms of originality, depth and relevance.