Results of Convergence, Stability, and Data Dependency for an Iterative Algorithm

In this study, we reconstruct an existing result related to the strong convergence of a recently introduced iterative algorithm by removing certain restrictions on the coefficient sequences. We then obtain some new results on the stability and data dependency of this algorithm. To validate our results, we provide a series of nontrivial complex examples, demonstrating the significance and accuracy of our theoretical contributions.

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Publication Details

Journal
Journal of New Theory
Published
2024-09-30
DOI
https://doi.org/10.53570/jnt.1537928
Citations
2
Primary Topic
Optimization and Variational Analysis
Type
article
Field-Weighted Citation Impact
0.72
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article

Results of Convergence, Stability, and Data Dependency for an Iterative Algorithm

Ayşegül Keten Çopur
2 citations
Journal of New Theory
Optimization and Variational Analysis
0.72
article

Results of Convergence, Stability, and Data Dependency for an Iterative Algorithm

Ayşegül Keten Çopur
article en
2 citations

Abstract

In this study, we reconstruct an existing result related to the strong convergence of a recently introduced iterative algorithm by removing certain restrictions on the coefficient sequences. We then obtain some new results on the stability and data dependency of this algorithm. To validate our results, we provide a series of nontrivial complex examples, demonstrating the significance and accuracy of our theoretical contributions.

Journal of New Theory(48)
Necmettin Erbakan University (TR)
Openalex Percentile: Top 26%
Optimization and Variational Analysis
0.72
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Results of Convergence, Stability, and Data Dependency for an Iterative Algorithm — Ayşegül Keten Çopur · Journal of New Theory (2024) | TGRS Research Map | TGRS