Max-Product Sampling Kantorovich Operators: Quantitative Estimates in Functional Spaces

In this paper, we study the order of approximation for max-product sampling Kantorovich operators based upon generalized kernels in the setting of Orlicz spaces. We establish a quantitative estimate for the considered family of sampling-type operators using the Orlicz-type modulus of smoothness, which involves the modular functional of the space. From this result, it is possible to obtain the qualitative order of convergence when functions belonging to suitable Lipschitz classes are considered. On the other hand, in the compact case, we exploit a suitable definition of K-functional in Orlicz spaces in order to provide an upper bound for the approximation error of the involved operators. The treatment in the general framework of Orlicz spaces allows one to obtain a unifying theory on the rate of convergence, as the proved results can be deduced for a wide range of functional spaces, such as Lp-spaces, interpolation spaces and exponential spaces.

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Publication Details

Journal
Numerical Functional Analysis and Optimization
Published
2024-10-06
DOI
https://doi.org/10.1080/01630563.2024.2405475
Citations
1
Primary Topic
Approximation Theory and Sequence Spaces
Type
article
Field-Weighted Citation Impact
0.71

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article

Max-Product Sampling Kantorovich Operators: Quantitative Estimates in Functional Spaces

Gianluca Vıntı, Danilo Costarellı, Lorenzo Boccali
1 citations
Numerical Functional Analysis and Optimization
Approximation Theory and Sequence Spaces
0.71
article

Max-Product Sampling Kantorovich Operators: Quantitative Estimates in Functional Spaces

Gianluca Vıntı, Danilo Costarellı, Lorenzo Boccali
article en
1 citations

Abstract

In this paper, we study the order of approximation for max-product sampling Kantorovich operators based upon generalized kernels in the setting of Orlicz spaces. We establish a quantitative estimate for the considered family of sampling-type operators using the Orlicz-type modulus of smoothness, which involves the modular functional of the space. From this result, it is possible to obtain the qualitative order of convergence when functions belonging to suitable Lipschitz classes are considered. On the other hand, in the compact case, we exploit a suitable definition of K-functional in Orlicz spaces in order to provide an upper bound for the approximation error of the involved operators. The treatment in the general framework of Orlicz spaces allows one to obtain a unifying theory on the rate of convergence, as the proved results can be deduced for a wide range of functional spaces, such as Lp-spaces, interpolation spaces and exponential spaces.

Numerical Functional Analysis and OptimizationVol. 45(13-14)
University of Perugia (IT), University of Florence (IT)
European Commission
Openalex Percentile: Top 26%
Approximation Theory and Sequence Spaces
0.71
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Max-Product Sampling Kantorovich Operators: Quantitative Estimates in Functional Spaces — Gianluca Vıntı, Danilo Costarellı, et al. · Numerical Functional Analysis and Optimization (2024) | TGRS Research Map | TGRS