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Weighted statistical rough convergence in normed spaces

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Názov: Weighted statistical rough convergence in normed spaces
Autori: Bayram, Erdal, Aydin, Abdullah, Kucukaslan, Mehmet
Informácie o vydavateľovi: Maejo Univ, 2024.
Rok vydania: 2024
Predmety: g-weight density, statistical rough convergence, limit points, normed spaces
Popis: Statistical convergence is a significant generalisation of the traditional convergence of real or complex valued sequences. Over the years, it has been studied by many authors and found many applications in various problems. In this paper we introduce a new concept about statistical rough convergence for sequences in normed spaces by using weighted density, which is a generalisation of the natural density. We investigate the fundamental properties of g-statistical rough convergence and statistical rough limit points including closeness, convexity and boundedness. We also establish a relationship between statistical rough limit points and g-statistical boundedness. The obtained results provide a new framework for studying statistical rough convergence.
Druh dokumentu: Article
Jazyk: English
Prístupová URL adresa: https://hdl.handle.net/20.500.12639/6730
Prístupové číslo: edsair.od......9656..8b7e6a8a9c5d10cd91a54110f0fa7958
Databáza: OpenAIRE
Popis
Abstrakt:Statistical convergence is a significant generalisation of the traditional convergence of real or complex valued sequences. Over the years, it has been studied by many authors and found many applications in various problems. In this paper we introduce a new concept about statistical rough convergence for sequences in normed spaces by using weighted density, which is a generalisation of the natural density. We investigate the fundamental properties of g-statistical rough convergence and statistical rough limit points including closeness, convexity and boundedness. We also establish a relationship between statistical rough limit points and g-statistical boundedness. The obtained results provide a new framework for studying statistical rough convergence.