New inertial self-adaptive algorithms for the split common null-point problem: application to data classifications

Autor:	Ratthaprom Promkam, Pongsakorn Sunthrayuth, Suparat Kesornprom, Ekapak Tanprayoon
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	p-uniformly convex Banach spaces Weak convergence Split common null-point problem Maximal monotone operator Self-adaptive algorithm Mathematics QA1-939
Zdroj:	Journal of Inequalities and Applications, Vol 2023, Iss 1, Pp 1-32 (2023)
Druh dokumentu:	article
ISSN:	1029-242X
DOI:	10.1186/s13660-023-03049-2
Popis:	Abstract In this paper, we propose two inertial algorithms with a new self-adaptive step size for approximating a solution of the split common null-point problem in the framework of Banach spaces. The step sizes are adaptively updated over each iteration by a simple process without the prior knowledge of the operator norm of the bounded linear operator. Under suitable conditions, we prove the weak-convergence results for the proposed algorithms in p-uniformly convex and uniformly smooth Banach spaces. Finally, we give several numerical results in both finite- and infinite-dimensional spaces to illustrate the efficiency and advantage of the proposed methods over some existing methods. Also, data classifications of heart diseases and diabetes mellitus are presented as the applications of our methods.
Databáze:	Directory of Open Access Journals
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