| Autor: |
Areerat Arunchai, Thidaporn Seangwattana, Kanokwan Sitthithakerngkiet, Kamonrat Sombut |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
AIMS Mathematics, Vol 8, Iss 4, Pp 9557-9575 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2473-6988 |
| DOI: |
10.3934/math.2023482?viewType=HTML?viewType=HTML |
| Popis: |
In this paper, we establish a modified proximal point algorithm for solving the common problem between convex constrained minimization and modified variational inclusion problems. The proposed algorithm base on the proximal point algorithm in [19] and the method of Khuangsatung and Kangtunyakarn in [21] by using suitable conditions in Hilbert spaces. The proposed algorithm is not only presented in this article; however has also been demonstrated to generate a robust convergence theorem. The proposed algorithm could be used to solve image restoration problems where the images have suffered a variety of blurring operations. Additionally, we contrast the signal-to-noise ratio (SNR) of the proposed algorithm against that of Khuangsatung and Kangtunyakarn's method in [21] in order to compare image quality. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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