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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
In this paper, we define the concepts of weighted lacunary �-statistical convergence or S I]I-summability, and investigate some inclusion relations.(,Rθ )( ) -convergence and [R p θ, , r
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper, we define the concepts of weighted lacunary �-statistical convergence or S I]I-summability, and investigate some inclusion relations.(,Rθ )( ) -convergence and [R p θ, , r
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Key Findings & Data:In this paper, we define the concepts of weighted lacunary �-statistical convergence or S I]I-summability, and investigate some inclusion relations.(,Rθ )( ) -convergence and [R p θ, , r
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Conclusion & Impact:In this paper, we define the concepts of weighted lacunary �-statistical convergence or S I]I-summability, and investigate some inclusion relations.(,Rθ )( ) -convergence and [R p θ, , r
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In this paper, we define the concepts of weighted lacunary �-statistical convergence or S I]I-summability, and investigate some inclusion relations.(,Rθ )( ) -convergence and [R p θ, , r
Özet
Bu makalede, S I veya ağırlıklı lacunary I-istatistiksel yakınsaklık ile [R p ?kavramları tanımlanmıştır ve bazı kapsama bağıntıları araştırılmıştır.(,R? )( ) ]I-toplanabilirlik r
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Cite This Article
KONCA, Ş. (2022). Ağırlıklı Lacunary I-İstatistiksel Yakınsaklık. Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Cilt: 7 - Sayı: 1, 267–277. https://ajindex.com/articles/538561