A Regularized Gradient Projection Method for the Minimization Problem
We investigate the following regularized gradient projection algorithm xn+1=Pc(I−γn(∇f+αnI))xn, n≥0. Under some different control conditions, we prove that this gradient projection algorithm strongly converges to the minimum norm solution of the minimization problem minx∈Cf(x).
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2012/259813 |
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| _version_ | 1832547534339309568 |
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| author | Yonghong Yao Shin Min Kang Wu Jigang Pei-Xia Yang |
| author_facet | Yonghong Yao Shin Min Kang Wu Jigang Pei-Xia Yang |
| author_sort | Yonghong Yao |
| collection | DOAJ |
| description | We investigate the following regularized gradient projection
algorithm xn+1=Pc(I−γn(∇f+αnI))xn, n≥0. Under some different control conditions, we prove that this gradient projection algorithm
strongly converges to the minimum norm solution of the minimization problem minx∈Cf(x). |
| format | Article |
| id | doaj-art-d30f7f929d074a6cbbede5ec3cd6dc2f |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-d30f7f929d074a6cbbede5ec3cd6dc2f2025-02-03T06:44:28ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/259813259813A Regularized Gradient Projection Method for the Minimization ProblemYonghong Yao0Shin Min Kang1Wu Jigang2Pei-Xia Yang3Department of Mathematics, Tianjin Polytechnic University, Tianjin 300387, ChinaDepartment of Mathematics and the RINS, Gyeongsang National University, Jinju 660-701, Republic of KoreaSchool of Computer Science and Software, Tianjin Polytechnic University, Tianjin 300387, ChinaDepartment of Mathematics, Tianjin Polytechnic University, Tianjin 300387, ChinaWe investigate the following regularized gradient projection algorithm xn+1=Pc(I−γn(∇f+αnI))xn, n≥0. Under some different control conditions, we prove that this gradient projection algorithm strongly converges to the minimum norm solution of the minimization problem minx∈Cf(x).http://dx.doi.org/10.1155/2012/259813 |
| spellingShingle | Yonghong Yao Shin Min Kang Wu Jigang Pei-Xia Yang A Regularized Gradient Projection Method for the Minimization Problem Journal of Applied Mathematics |
| title | A Regularized Gradient Projection Method for the Minimization Problem |
| title_full | A Regularized Gradient Projection Method for the Minimization Problem |
| title_fullStr | A Regularized Gradient Projection Method for the Minimization Problem |
| title_full_unstemmed | A Regularized Gradient Projection Method for the Minimization Problem |
| title_short | A Regularized Gradient Projection Method for the Minimization Problem |
| title_sort | regularized gradient projection method for the minimization problem |
| url | http://dx.doi.org/10.1155/2012/259813 |
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