Rough statistical cluster points

Filomat ◽  
2017 ◽  
Vol 31 (16) ◽  
pp. 5295-5304
Author(s):  
Salih Aytar
Keyword(s):  
Statistical Convergence ◽  
Cluster Point ◽  
Convergence Criteria ◽  
Finite Dimensional ◽  
Statistical Cluster ◽  
Statistical Limit ◽  
Condensation Point ◽  
Statistical Cluster Point ◽  
Dimensional Normed Space ◽  
Cluster Points

In this paper, we define the concepts of rough statistical cluster point and rough statistical limit point of a sequence in a finite dimensional normed space. Then we obtain an ordinary statistical convergence criteria associated with rough statistical cluster point of a sequence. Applying these definitions to the sequences of functions, we come across a new concept called statistical condensation point. Finally, we observe the relations between the sets of statistical condensation points, rough statistical cluster points and rough statistical limit points of a sequence of functions.

scholarly journals Statistical convergence of double sequences in fuzzy normed spaces

Filomat ◽  
2012 ◽  
Vol 26 (4) ◽  
pp. 673-681 ◽  
Author(s):  
S.A. Mohiuddine ◽  
H. Şevli ◽  
M. Cancan
Keyword(s):  
Limit Point ◽  
General Class ◽  
Statistical Convergence ◽  
Cluster Point ◽  
Double Sequences ◽  
Normed Spaces ◽  
Statistical Cluster ◽  
Statistical Limit ◽  
Statistical Cluster Point ◽  
The Relationship

In this paper, we study the concepts of statistically convergent and statistically Cauchy double sequences in the framework of fuzzy normed spaces which provide better tool to study a more general class of sequences. We also introduce here statistical limit point and statistical cluster point for double sequences in this framework and discuss the relationship between them.

When deviation happens between rough statistical convergence and rough weighted statistical convergence

2019 ◽  
Vol 69 (4) ◽  
pp. 871-890 ◽  
Author(s):  
Sanjoy Ghosal ◽  
Avishek Ghosh
Keyword(s):  
Statistical Convergence ◽  
Limit Set ◽  
Double Sequences ◽  
Statistical Cluster ◽  
Statistical Limit ◽  
Cluster Points

Abstract In this paper we introduce rough weighted statistical limit set and weighted statistical cluster points set which are natural generalizations of rough statistical limit set and statistical cluster points set of double sequences respectively. Some new examples are constructed to ensure the deviation of basic results. Both the sets don’t follow the usual extension properties which will be discussed here.

scholarly journals Effects on rough I-lacunary statistical convergence to induce the weighted sequence

Filomat ◽  
2018 ◽  
Vol 32 (10) ◽  
pp. 3557-3568 ◽  
Author(s):  
Sanjoy Ghosal ◽  
Mandobi Banerjee
Keyword(s):  
Statistical Convergence ◽  
Limit Set ◽  
Topological Approach ◽  
Weighted Sequence ◽  
Statistical Cluster ◽  
Statistical Limit ◽  
Lacunary Statistical Convergence ◽  
Cluster Points

Two classes of sets are introduced: rough weighted I-lacunary statistical limit set and weighted I-lacunary statistical cluster points set which are natural generalizations of rough I-limit set and I-cluster points set respectively. To highlight the variation from basic results we place into some new examples. So our aim is to analyze the different behaviors of the new convergences and characterize both the sets with topological approach like closedness, boundedness, compactness etc.

Some further studies on strong ℐλ-statistical convergence in probabilistic metric spaces

Analysis ◽  
2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Argha Ghosh ◽  
Samiran Das
Keyword(s):  
Statistical Convergence ◽  
Metric Spaces ◽  
Cluster Point ◽  
Probabilistic Metric Spaces ◽  
Basic Properties ◽  
Statistical Cluster ◽  
Cauchy Sequences ◽  
Convergence Of Sequences ◽  
Statistical Cluster Point ◽  
Probabilistic Metric

Abstract We prove some basic properties of strong ℐ λ {\mathcal{I}_{\lambda}} -statistical convergence of sequences in probabilistic metric spaces and introduce the notion of strong ℐ λ {\mathcal{I}_{\lambda}} -statistical cluster point. We also introduce the notion of strong ℐ λ {\mathcal{I}_{\lambda}} -statistical Cauchy sequences in probabilistic metric spaces. Further, we establish a connection between strong ℐ λ {\mathcal{I}_{\lambda}} -statistical convergence and strong ℐ λ {\mathcal{I}_{\lambda}} -statistical Cauchy sequences.

scholarly journals Statistical Cluster Points of Sequences in Finite Dimensional Spaces

2004 ◽  
Vol 54 (1) ◽  
pp. 95-102 ◽  
Author(s):  
S. Pehlivan ◽  
A. Güncan ◽  
M. A. Mamedov
Keyword(s):  
Finite Dimensional ◽  
Statistical Cluster ◽  
Cluster Points

scholarly journals On Cluster Points, Continuity, and Boundedness Associated with the Generalized Statistical Convergence in Probabilistic Normed Spaces

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Pratulananda Das ◽  
Kaustubh Dutta ◽  
Vatan Karakaya
Keyword(s):  
Statistical Convergence ◽  
Normed Spaces ◽  
Statistical Cluster ◽  
Probabilistic Normed Spaces ◽  
Extremal Limit ◽  
Limit Points ◽  
Appl Math ◽  
Cluster Points

We consider the recently introduced notion ofℐ-statistical convergence (Das, Savas and Ghosal, Appl. Math. Lett., 24(9) (2011), 1509–1514, Savas and Das, Appl. Math. Lett. 24(6) (2011), 826–830) in probabilistic normed spaces and in the following (Şençimen and Pehlivan (2008 vol. 26, 2008 vol. 87, 2009)) we introduce the notions like strongℐ-statistical cluster points and extremal limit points, and strongℐ-statistical continuity and strongℐ-statisticalD-boundedness in probabilistic normed spaces and study some of their important properties.

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