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.
Authors
- Gianluca Vıntı (ORCID: https://orcid.org/0000-0002-9875-2790)
- Danilo Costarellı (ORCID: https://orcid.org/0000-0001-8834-8877)
- Lorenzo Boccali
Institutions
- University of Perugia (IT)
- University of Florence (IT)
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
Funders
- European Commission