arXiv subjects

Satyaranjan Pradhan

Publications and source records attributed to Satyaranjan Pradhan.

5 recordsLinked to original sources

arXiv2025

Convergence analysis of max-product and max-min Durrmeyer-type exponential sampling operators in Mellin Orlicz space

In the present study, we establish both pointwise and uniform convergence in the space of logarithmically uniformly continuous and bounded functions for the max-product and max-min Durrmeyer-type exponential sampling operators. Furthermore, the modular convergence of these operators is demonstrated within the framework of Orlicz space. In addition to the theoretical results, we provide numerical and graphical analyses for various kernel pairs, illustrating the convergence rates and approximation behavior of the proposed operators.

math.FA↗

arXiv2025

On the Convergence of Max-product and Max-Min Durrmeyer-type Exponential Sampling Operators

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 continuous and bounded functions. The rates of convergence are then analyzed in terms of the logarithmic modulus of continuity. Additionally, the approximation errors of the proposed operators are examined using a variety of kernel functions. Finally, graphical illustrations are provided to demonstrate the convergence behavior of both operators.

math.FA↗

arXiv2025

Convergence Analysis of Max-Min Exponential Neural Network Operators in Orlicz Space

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 investigate their approximation properties. We study both pointwise and uniform convergence for univariate functions. To analyze the order of convergence, we use the logarithmic modulus of continuity and estimate the corresponding rate of convergence. Furthermore, we examine the convergence behavior of the Max Min Kantorovich type exponential neural network operators within the Orlicz space setting. We provide some graphical representations to illustrate the approximation error of the function through suitable kernel and sigmoidal activation functions.

cs.LG↗

arXiv2025

Weighted approximation By Max-product Kantrovich type Exponential Sampling Series

In this study, we examine the convergence characteristics of the Max-Product Kantrovich type exponential sampling series within the weighted space of log-uniformly continuous and bounded functions. The research focuses on deriving fundamental convergence results for the series and analyzing its asymptotic convergence behavior. The study estimates the rate of convergence using the weighted logarithmic modulus of continuity and establishes a quantitative Voronovskaja-type theorem offering insights into the asymptotic behavior of the series. Additionally, we present the example of kernel functions satisfying assumptions of the presented theory along with graphical demonstration and estimates of approximation.

math.FA↗

arXiv2024

Weighted Approximation By Max-Product Generalized Exponential Sampling Series

In this article, we study the convergence behaviour of the classical generalized Max Product exponential sampling series in the weighted space of log-uniformly continuous and bounded functions. We derive basic convergence results for both the series and study the asymptotic convergence behaviour. Some quantitative approximation results have been obtained utilizing the notion of weighted logarithmic modulus of continuity.

math.FA↗