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Strong Gamma-Statistical Convergence in Probabilistic Normed Spaces

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dc.creator ŞENÇİMEN, CELALEDDİN
dc.creator PEHLİVAN, Serpil
dc.date 2016-11-30T21:00:00Z
dc.date.accessioned 2020-10-06T11:50:35Z
dc.date.available 2020-10-06T11:50:35Z
dc.identifier f17a23e8-3802-4bd3-9677-ea905f9eec60
dc.identifier 10.1007/s40306-015-0158-4
dc.identifier https://avesis.sdu.edu.tr/publication/details/f17a23e8-3802-4bd3-9677-ea905f9eec60/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/75904
dc.description The concept of statistical cluster point of a sequence which presents random deviations is very important in the study of optimal paths and turnpike theory. In this study, we investigate some properties of the set of all strong statistical cluster points of a sequence in a probabilistic normed (PN) space in which the norms of the vectors are represented by probability distribution functions due to randomness. In this context, we also introduce the concept of strong I"-statistical convergence in a PN space, and examine some of its basic properties.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Strong Gamma-Statistical Convergence in Probabilistic Normed Spaces
dc.type info:eu-repo/semantics/article


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