An improved fast iterative shrinkage thresholding algorithm with an error for image deblurring problem

Autor:	Pattanapong Tianchai
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	Variational inclusion problem Maximal monotone operator Forward-backward method Iterative shrinkage thresholding Image deblurring problem Applied mathematics. Quantitative methods T57-57.97 Analysis QA299.6-433
Zdroj:	Fixed Point Theory and Algorithms for Sciences and Engineering, Vol 2021, Iss 1, Pp 1-25 (2021)
Druh dokumentu:	article
ISSN:	2730-5422
DOI:	10.1186/s13663-021-00703-6
Popis:	Abstract In this paper, we introduce a new iterative forward-backward splitting method with an error for solving the variational inclusion problem of the sum of two monotone operators in real Hilbert spaces. We suggest and analyze this method under some mild appropriate conditions imposed on the parameters such that another strong convergence theorem for these problem is obtained. We also apply our main result to improve the fast iterative shrinkage thresholding algorithm (IFISTA) with an error for solving the image deblurring problem. Finally, we provide numerical experiments to illustrate the convergence behavior and show the effectiveness of the sequence constructed by the inertial technique to the fast processing with high performance and the fast convergence with good performance of IFISTA.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/4735e8850a44468193aa14c08b2abfff Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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