Rough Weighted Ideal Convergence and Korovkin-Type Approximation via weighted equi-ideal convergence
Abstract
If ωt > β for every t ∈ N and for some β > 0, then the sequence \ωt\t ∈ N represents a weighted sequence of real numbers. In this article, we primarily introduce the concepts of rough weighted ideal limit set and rough weighted ideal cluster points set associated with sequences in normed spaces. Building on these concepts, we derive several important results, including a characterization of maximal ideals, a representation of closed sets in normed spaces, and an analysis of the minimal convergent degree required for the rough weighted ideal limit set to be non-empty. Furthermore, we demonstrate that for an analytic P-ideal, the rough weighted ideal limit set forms an Fσδ subset of the normed space. Finally, we introduce the concept of weighted equi-ideal convergence for sequences of functions with respect to analytic P-ideals, extending the notion of equi-statistical convergence [Balcerzak et al., J. Math. Anal. Appl. 328 (1) (2007)]. As an application of this notion, we establish a Korovkin-type approximation theorem that serves both as a generalization of [Theorem 2.4, Karakus et al., J. Math. Anal. Appl. 339 (2) (2008)] and a correction to [Theorem 2.2, Akdag, Results Math. 72 (3) (2017)].
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.