On strong AI-statistical convergence of sequences in probabilistic metric spaces

Abstract

In this paper using a non-negative regular summability matrix A and a non-trivial admissible ideal I in N we study some basic properties of strong AI-statistical convergence and strong AI-statistical Cauchyness of sequences in probabilistic metric spaces not done earlier. We also introduce strong AI*-statistical Cauchyness in probabilistic metric space and study its relationship with strong AAI-statistical Cauchyness there. Further, we study some basic properties of strong AI-statistical limit points and strong AI-statistical cluster points of a sequence in probabilistic metric spaces.

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