An Efficient Iterative Algorithm for Solving the Split Feasibility Problem in Hilbert Spaces Applicable in Image Deblurring, Signal Recovering, and Polynomiography
The split feasibility problem (SFP) in Hilbert spaces is addressed in this study using an efficient iterative approach. Under mild conditions, we prove convergence theorems for the algorithm for finding a solution to the SFP. We also present numerical examples to illustrate that the acceleration of...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2023-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2023/4934575 |
| _version_ | 1797836791437328384 |
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| author | Lanchakorn Kittiratanawasin Damrongsak Yambangwai Chonjaroen Chairatsiripong Tanakit Thianwan |
| author_facet | Lanchakorn Kittiratanawasin Damrongsak Yambangwai Chonjaroen Chairatsiripong Tanakit Thianwan |
| author_sort | Lanchakorn Kittiratanawasin |
| collection | DOAJ |
| description | The split feasibility problem (SFP) in Hilbert spaces is addressed in this study using an efficient iterative approach. Under mild conditions, we prove convergence theorems for the algorithm for finding a solution to the SFP. We also present numerical examples to illustrate that the acceleration of our algorithm is effective. Our results are applied to solve image deblurring and signal recovery problems. Furthermore, we show the use of the proposed method to generate polynomiographs. |
| first_indexed | 2024-04-09T15:15:41Z |
| format | Article |
| id | doaj.art-0652f88aafcc4ee59901a1fcce0be678 |
| institution | Directory Open Access Journal |
| issn | 2314-4785 |
| language | English |
| last_indexed | 2024-04-09T15:15:41Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi Limited |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj.art-0652f88aafcc4ee59901a1fcce0be6782023-04-30T00:00:07ZengHindawi LimitedJournal of Mathematics2314-47852023-01-01202310.1155/2023/4934575An Efficient Iterative Algorithm for Solving the Split Feasibility Problem in Hilbert Spaces Applicable in Image Deblurring, Signal Recovering, and PolynomiographyLanchakorn Kittiratanawasin0Damrongsak Yambangwai1Chonjaroen Chairatsiripong2Tanakit Thianwan3Department of MathematicsDepartment of MathematicsDepartment of MathematicsDepartment of MathematicsThe split feasibility problem (SFP) in Hilbert spaces is addressed in this study using an efficient iterative approach. Under mild conditions, we prove convergence theorems for the algorithm for finding a solution to the SFP. We also present numerical examples to illustrate that the acceleration of our algorithm is effective. Our results are applied to solve image deblurring and signal recovery problems. Furthermore, we show the use of the proposed method to generate polynomiographs.http://dx.doi.org/10.1155/2023/4934575 |
| spellingShingle | Lanchakorn Kittiratanawasin Damrongsak Yambangwai Chonjaroen Chairatsiripong Tanakit Thianwan An Efficient Iterative Algorithm for Solving the Split Feasibility Problem in Hilbert Spaces Applicable in Image Deblurring, Signal Recovering, and Polynomiography Journal of Mathematics |
| title | An Efficient Iterative Algorithm for Solving the Split Feasibility Problem in Hilbert Spaces Applicable in Image Deblurring, Signal Recovering, and Polynomiography |
| title_full | An Efficient Iterative Algorithm for Solving the Split Feasibility Problem in Hilbert Spaces Applicable in Image Deblurring, Signal Recovering, and Polynomiography |
| title_fullStr | An Efficient Iterative Algorithm for Solving the Split Feasibility Problem in Hilbert Spaces Applicable in Image Deblurring, Signal Recovering, and Polynomiography |
| title_full_unstemmed | An Efficient Iterative Algorithm for Solving the Split Feasibility Problem in Hilbert Spaces Applicable in Image Deblurring, Signal Recovering, and Polynomiography |
| title_short | An Efficient Iterative Algorithm for Solving the Split Feasibility Problem in Hilbert Spaces Applicable in Image Deblurring, Signal Recovering, and Polynomiography |
| title_sort | efficient iterative algorithm for solving the split feasibility problem in hilbert spaces applicable in image deblurring signal recovering and polynomiography |
| url | http://dx.doi.org/10.1155/2023/4934575 |
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