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Approximation properties of the sampling-type quasi-projection operators $Q_j(f,\varphi, \widetilde{\varphi})$ for functions $f$ from anisotropic Besov spaces are studied. Error estimates in $L_p$-norm are obtained for a large class of…

Classical Analysis and ODEs · Mathematics 2020-01-27 Yurii Kolomoitsev , Maria Skopina

The purpose of this paper is to study the approximation of vector valued mappings defined on a subset of a normed space. We investigate Korovkin-type conditions under which a given sequence of linear operators becomes a so-called…

Functional Analysis · Mathematics 2007-05-23 Lorenzo D'Ambrosio

This article discusses the convergence properties of the Max Product and Max Min variants of Durrmeyer type exponential sampling series. We first establish pointwise and uniform convergence of both operators in the space of log uniformly…

Functional Analysis · Mathematics 2025-10-17 Satyaranjan Pradhan , Abhishek Senapati , Madan Mohan Soren

The present paper deals with construction of newly family of Neural Network operators, that is, Steklov Neural Network operators. By using Steklov type integral, we introduce a new version of Neural Network operators and we obtain some…

Functional Analysis · Mathematics 2024-12-18 S. N. Karaman , M. Turgay , T. Acar

In this paper, we investigate the approximation properties of the summation-integral type operators as defined by Mishra et al. (Boll. Unione Mat. Ital. (2016) 8:297-305) and determine the local results as well as prove the convergence…

Functional Analysis · Mathematics 2020-02-25 Rishikesh Yadav , Ramakanta Meher , Vishnu Narayan Mishra

Approximation properties of multivariate quasi-projection operators are studied in the paper. Wide classes of such operators are considered, including the sampling and the Kantorovich-Kotelnikov type operators generated by different…

Classical Analysis and ODEs · Mathematics 2020-03-26 Yurii Kolomoitsev , Maria Skopina

Traditional measures of smoothness often fail to provide accurate $L_p$-error estimates for approximation by sampling or interpolation operators, especially for functions with low smoothness. To address this issue, we introduce a modified…

Numerical Analysis · Mathematics 2025-07-02 Yurii Kolomoitsev

This survey paper contains a detailed self-contained introduction to Korovkin-type theorems and to some of their applications concerning the approximation of continuous functions as well as of L^p-functions, by means of positive linear…

Classical Analysis and ODEs · Mathematics 2010-09-15 Francesco Altomare

Here we introduce a generalization of the exponential sampling series of optical physics and establish pointwise and uniform convergence theorem, also in a quantitative form. Moreover we compare the error of approximation for Mellin…

Functional Analysis · Mathematics 2016-10-03 Carlo Bardaro , Loris Faina , Ilaria Mantellini

We solve the Stechkin problem about approximation of generally speaking unbounded hypersingular integral operators by bounded ones. As a part of the proof, we also solve several related and interesting on their own problems. In particular,…

Functional Analysis · Mathematics 2022-06-06 Vladyslav Babenko , Oleg Kovalenko , Nataliia Parfinovych

This article is the second one of three successive articles of the authors on the matrix-weighted Besov-type and Triebel--Lizorkin-type spaces. In this article, we obtain the sharp boundedness of almost diagonal operators on matrix-weighted…

Functional Analysis · Mathematics 2024-08-22 Fan Bu , Tuomas Hytönen , Dachun Yang , Wen Yuan

In this paper multivariate extension of the generalized Durrmeyer sampling type series are considered. We establish a Voronovskaja type formula and a quantitative version. Finally some particular examples are discussed.

Functional Analysis · Mathematics 2016-05-25 Carlo Bardaro , Ilaria Mantellini

We study resolvent approximations for elliptic differential nonselfadjoint operators with periodic coefficients in the limit of the small period. The class of operators covered by our analysis includes uniformly elliptic families with…

Analysis of PDEs · Mathematics 2020-01-07 Svetlana Pastukhova

We analyse the approximation properties of the bivariate generalization of the family of Kantorovich type exponential sampling series. We derive the point-wise and Voronovskaya type theorem for these sampling type series. Using the modulus…

Functional Analysis · Mathematics 2020-07-21 Prashant Kumar , A. Sathish Kumar , Shivam Bajpyei

We introduce certain linear positive operators and study some approximation properties of these operators in the space of functions, continuous on a compact set, of two variables. We also find the order of this approximation by using…

Classical Analysis and ODEs · Mathematics 2007-09-24 Fatma Tasdelen , Ali Olgun , Gulen Bascanbaz-Tunca

This paper studies approximation properties of linear sampling operators in general Banach lattices $X$. We obtain matching direct and inverse approximation estimates, convergence criteria, equivalence results involving special…

Functional Analysis · Mathematics 2026-01-28 Yurii Kolomoitsev

We introduce and study a family of integral operators in the Kantorovich sense for functions acting on locally compact topological groups. We obtain convergence results for the above operators with respect to the pointwise and uniform…

Functional Analysis · Mathematics 2014-08-26 Gianluca Vinti , Luca Zampogni

We give some Korovkin-type theorems on convergence and estimates of rates of approximations of nets of functions, satisfying suitable axioms, whose particular cases are filter/ideal convergence, almost convergence and triangular…

Functional Analysis · Mathematics 2021-01-15 Antonio Boccuto , Xenofon Dimitriou

In the present article, we deal with the overconvergence of the Sz?asz-Durrmeyer-Chlodowsky operators. Here we study the approximation properties e.g. upper estimates, Voronovskaja type result for these operators attached to analytic…

Classical Analysis and ODEs · Mathematics 2016-05-19 Meenu Goyal , P. N. Agrawal

In this current work, we propose a Max Min approach for approximating functions using exponential neural network operators. We extend this framework to develop the Max Min Kantorovich-type exponential neural network operators and…

Machine Learning · Computer Science 2025-08-15 Satyaranjan Pradhan , Madan Mohan Soren