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Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
DBLP
Article . 2025
Data sources: DBLP
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Characterization of the Best Approximation and Establishment of the Best Proximity Point Theorems in Lorentz Spaces

Authors: Dezhou Kong; Zhihao Xu; Yun Wang 0017; Li Sun;

Characterization of the Best Approximation and Establishment of the Best Proximity Point Theorems in Lorentz Spaces

Abstract

Since the monotonicity of the best approximant is crucial to establish partial ordering methods, in this paper, we, respectively, characterize the best approximants in Banach function spaces and Lorentz spaces Γp,w, in which we especially focus on the monotonicity characterizations. We first study monotonicity characterizations of the metric projection operator onto sublattices in general Banach function spaces by the property Hg. The sufficient and necessary conditions for monotonicity of the metric projection onto cones and sublattices are then, respectively, established in Γp,w. The Lorentz spaces Γp,w are also shown to be reflexive under the condition RBp, which is the basis for the existence of the best approximant. As applications, by establishing the partial ordering methods based on the obtained monotonicity characterizations, the solvability and approximation theorems for best proximity points are deduced without imposing any contractive and compact conditions in Γp,w. Our results extend and improve many previous results in the field of the approximation and partial ordering theory.

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Keywords

monotone, Lorentz space, Banach function space, metric projection, best approximation

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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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