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Algorithms
Article . 2022 . Peer-reviewed
License: CC BY
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Algorithms
Article . 2022
Data sources: DOAJ
DBLP
Article . 2023
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On the Semi-Local Convergence of Two Competing Sixth Order Methods for Equations in Banach Space

Authors: Ioannis K. Argyros; Stepan Shakhno; Samundra Regmi; Halyna Yarmola;

On the Semi-Local Convergence of Two Competing Sixth Order Methods for Equations in Banach Space

Abstract

A plethora of methods are used for solving equations in the finite-dimensional Euclidean space. Higher-order derivatives, on the other hand, are utilized in the calculation of the local convergence order. However, these derivatives are not on the methods. Moreover, no bounds on the error and uniqueness information for the solution are given either. Thus, the advantages of these methods are restricted in their application to equations with operators that are sufficiently many times differentiable. These limitations motivate us to write this paper. In particular, we present the more interesting semi-local convergence analysis not given previously for two sixth-order methods that are run under the same set of conditions. The technique is based on the first derivative that only appears in the methods. This way, these methods are more applicable for addressing equations and in the more general setting of Banach space-valued operators. Hence, the applicability is extended for these methods. This is the novelty of the paper. The same technique can be used in other methods. Finally, examples are used to test the convergence of the methods.

Keywords

Banach spaces, Fréchet derivative, Industrial engineering. Management engineering, convergence ball, Electronic computers. Computer science, semi-local convergence, QA75.5-76.95, Banach spaces; Fréchet derivative; convergence order; semi-local convergence; convergence ball, T55.4-60.8, convergence order

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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