• An inertial parallel algorithm...

Treffer: An inertial parallel algorithm for a finite family of G-nonexpansive mappings applied to signal recovery

Title:
An inertial parallel algorithm for a finite family of G-nonexpansive mappings applied to signal recovery
Authors:
Nipa Jun-on, Raweerote Suparatulatorn, Mohamed Gamal, Watcharaporn Cholamjiak
Source:
AIMS Mathematics, Vol 7, Iss 2, Pp 1775-1790 (2022)
Publisher Information:
AIMS Press, 2022.
Publication Year:
2022
Collection:
LCC:Mathematics
Subject Terms:
weak convergence, parallel algorithm, g-nonexpansive, inertial extrapolation, numerical discussion, Mathematics, QA1-939
Document Type:
Fachzeitschrift article
File Description:
electronic resource
Language:
English
ISSN:
2473-6988
Relation:
https://doaj.org/toc/2473-6988
DOI:
10.3934/math.2022102?viewType=HTML
DOI:
10.3934/math.2022102
Access URL:
https://doaj.org/article/8d901321a3f746ce9932b89beb0ca8a7
Accession Number:
edsdoj.8d901321a3f746ce9932b89beb0ca8a7
Database:
Directory of Open Access Journals

Weitere Informationen

This study investigates the weak convergence of the sequences generated by the inertial technique combining the parallel monotone hybrid method for finding a common fixed point of a finite family of G-nonexpansive mappings under suitable conditions in Hilbert spaces endowed with graphs. Some numerical examples are also presented, providing applications to signal recovery under situations without knowing the type of noises. Besides, numerical experiments of the proposed algorithms, defined by different types of blurred matrices and noises on the algorithm, are able to show the efficiency and the implementation for LASSO problem in signal recovery.