Lacunary Statistical Convergence in Measure for Double Sequences of Fuzzy Valued Functions
Author(s) -
Ömer Kı̇şı̇
Publication year - 2021
Publication title -
journal of mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.252
H-Index - 13
eISSN - 2314-4785
pISSN - 2314-4629
DOI - 10.1155/2021/6655630
Subject(s) - lacunary function , mathematics , measure (data warehouse) , convergence (economics) , sequence (biology) , fuzzy logic , discrete mathematics , artificial intelligence , data mining , computer science , genetics , biology , economics , economic growth
Based on the concept of lacunary statistical convergence of sequences of fuzzy numbers, the lacunary statistical convergence, uniformly lacunary statistical convergence, and equi-lacunary statistical convergence of double sequences of fuzzy-valued functions are defined and investigated in this paper. The relationship among lacunary statistical convergence, uniformly lacunary statistical convergence, equi-lacunary statistical convergence of double sequences of fuzzy-valued functions, and their representations of sequences of - level cuts are discussed. In addition, we obtain the lacunary statistical form of Egorov’s theorem for double sequences of fuzzy-valued measurable functions in a finite measurable space. Finally, the lacunary statistical convergence in measure for double sequences of fuzzy-valued measurable functions is examined, and it is proved that the inner and outer lacunary statistical convergence in measure are equivalent in a finite measure set for a double sequence of fuzzy-valued measurable functions.
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