Strong convergence of an inertial extrapolation method for a split system of minimization problems

Abstract: In this article, we propose an inertial extrapolation-type algorithm for solving split system of minimization problems: finding a common minimizer point of a finite family of proper, lower semicontinuous convex functions and whose image under a linear transformation is also common minimizer point of another finite family of proper, lower semicontinuous convex functions. The strong convergence theorem is given in such a way that the step sizes of our algorithm are selected without the need for any prior information about the operator norm. The results obtained in this article improve and extend many recent ones in the literature. Finally, we give one numerical example to demonstrate the efficiency and implementation of our proposed algorithm.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Strong convergence of an inertial extrapolation method for a split system of minimization problems ; volume:53 ; number:1 ; year:2020 ; pages:332-351 ; extent:20
Demonstratio mathematica ; 53, Heft 1 (2020), 332-351 (gesamt 20)

Creator
Gebrie, Anteneh Getachew
Wangkeeree, Rabian

DOI
10.1515/dema-2020-0025
URN
urn:nbn:de:101:1-2411181518014.511414957479
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:35 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Associated

  • Gebrie, Anteneh Getachew
  • Wangkeeree, Rabian

Other Objects (12)