Introducing Statistical Operators: Boundedness, Continuity, and Compactness
Erdal Bayram, Mehmet K\"u\c{c}\"ukaslan, Mikail Et, Abdullah Ayd{\i}n

TL;DR
This paper introduces the concepts of statistical boundedness, continuity, and compactness for operators between normed spaces, establishing their relationships with classical operator theory and exploring their properties.
Contribution
It is the first to systematically study statistical operator properties, bridging statistical convergence with traditional operator theory in normed spaces.
Findings
Defined statistical boundedness, continuity, and compactness for operators.
Established connections between statistical and classical operator concepts.
Provided examples illustrating statistical operator behavior.
Abstract
Many studies have been conducted on statistical convergence, and it remains an area of active research. Since its introduction, statistical convergence has found applications many fields. Nevertheless, there is a shortage of research related to operator theory. As far as we know, no studies have focused on continuous, bounded, and compact operators, which are fundamental concepts in mathematics. We explore the notions of statistical boundedness, continuity, and compactness of operators between normed spaces, establishing connections between these concepts and their counterparts in traditional normed space theory. Additionally, we provide examples and results that demonstrate the behavior and implications of statistical convergence in the context of operators.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNeural Networks and Applications
