Regularized Methods for the Split Feasibility Problem
Many applied problems such as image reconstructions and signal processing can be formulated as the split feasibility problem (SFP). Some algorithms have been introduced in the literature for solving the (SFP). In this paper, we will continue to consider the convergence analysis of the regularized me...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2012/140679 |
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| _version_ | 1832565799186857984 |
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| author | Yonghong Yao Wu Jigang Yeong-Cheng Liou |
| author_facet | Yonghong Yao Wu Jigang Yeong-Cheng Liou |
| author_sort | Yonghong Yao |
| collection | DOAJ |
| description | Many applied problems such as image reconstructions and signal processing can
be formulated as the split feasibility problem (SFP). Some algorithms have been introduced in the literature for solving the (SFP). In this paper, we will continue to consider the convergence analysis of the regularized methods for the (SFP). Two
regularized methods are presented in the present paper. Under some different control
conditions, we prove that the suggested algorithms strongly converge to the minimum
norm solution of the (SFP). |
| format | Article |
| id | doaj-art-8d8b8b719aed4130a25ae5b72ec7256f |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-8d8b8b719aed4130a25ae5b72ec7256f2025-02-03T01:06:44ZengWileyAbstract and Applied Analysis1085-33751687-04092012-01-01201210.1155/2012/140679140679Regularized Methods for the Split Feasibility ProblemYonghong Yao0Wu Jigang1Yeong-Cheng Liou2Department of Mathematics, Tianjin Polytechnic University, Tianjin 300387, ChinaSchool of Computer Science and Software, Tianjin Polytechnic University, Tianjin 300387, ChinaDepartment of Information Management, Cheng Shiu University, Kaohsiung 833, TaiwanMany applied problems such as image reconstructions and signal processing can be formulated as the split feasibility problem (SFP). Some algorithms have been introduced in the literature for solving the (SFP). In this paper, we will continue to consider the convergence analysis of the regularized methods for the (SFP). Two regularized methods are presented in the present paper. Under some different control conditions, we prove that the suggested algorithms strongly converge to the minimum norm solution of the (SFP).http://dx.doi.org/10.1155/2012/140679 |
| spellingShingle | Yonghong Yao Wu Jigang Yeong-Cheng Liou Regularized Methods for the Split Feasibility Problem Abstract and Applied Analysis |
| title | Regularized Methods for the Split Feasibility Problem |
| title_full | Regularized Methods for the Split Feasibility Problem |
| title_fullStr | Regularized Methods for the Split Feasibility Problem |
| title_full_unstemmed | Regularized Methods for the Split Feasibility Problem |
| title_short | Regularized Methods for the Split Feasibility Problem |
| title_sort | regularized methods for the split feasibility problem |
| url | http://dx.doi.org/10.1155/2012/140679 |
| work_keys_str_mv | AT yonghongyao regularizedmethodsforthesplitfeasibilityproblem AT wujigang regularizedmethodsforthesplitfeasibilityproblem AT yeongchengliou regularizedmethodsforthesplitfeasibilityproblem |