On Strong A-statistical Convergence in Probabilistic Metric Spaces
Prasanta Malik, Samiran Das
TL;DR
This paper investigates properties of strong A-statistical convergence and related concepts in probabilistic metric spaces, introducing new notions and exploring their relationships to deepen understanding of convergence behaviors.
Contribution
It introduces the concept of strong statistically A-summable sequences and explores their connection with strong A-statistical convergence in probabilistic metric spaces.
Findings
Established basic properties of strong A-statistical convergence.
Analyzed strong A-statistical Cauchyness and limit points.
Introduced and studied strong statistically A-summable sequences.
Abstract
In this paper we study some basic properties of strong A-statistical convergence and strong A-statistical Cauchyness of sequences in probabilistic metric spaces not done earlier. We also study some basic properties of strong A-statistical limit points and strong A-statistical cluster points of a sequence in a probabilistic metric space. Further we also introduce the notion of strong statistically A-summable sequence in a probabilistic metric space and study its relationship with strong A-statistical convergence.
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Taxonomy
TopicsApproximation Theory and Sequence Spaces · Fixed Point Theorems Analysis · Fuzzy and Soft Set Theory