Modified Kantorovich-type Sampling Series in Orlicz Space Frameworks

This study examines a modified Kantorovich approach applied to generalized sampling series. The paper establishes that the approximation order to a function using these modified operators is atleast as good as that achieved by classical methods by using some graphs. The analysis focuses on these series within the context of Orlicz space $L^{\eta}(\mathbb{R})$, specifically looking at irregularly spaced samples. This is crucial for real-world applications, especially in fields like signal processing and computational mathematics, where samples are often not uniformly spaced. The paper also establishes a result on modular convergence for functions $g \in L^{\eta}(\mathbb{R})$, which includes specific cases like convergence in $L^{p}(\mathbb{R})$-spaces, $L \log L$-spaces, and exponential spaces. The study then explores practical applications of the modified sampling series, notably for discontinuous functions and provides graphs to illustrate the results.