Exploring a Novel Approach to Deferred Nörlund Statistical Convergence

Ibrahim Sulaiman Ibrahim, Ji-Huan He, Nejmeddine Chorfi, Majeed Ahmad Yousif, Pshtiwan Othman Mohammed, Miguel Vivas-Cortez

Research output: Contribution to journalArticlepeer-review

Abstract

This study introduces novel concepts of convergence and summability for numerical sequences, grounded in the newly formulated deferred Nörlund density, and explores their intrinsic connections to symmetry in mathematical structures. By leveraging symmetry principles inherent in sequence behavior and employing two distinct modulus functions under varying conditions, profound links between sequence convergence and summability are established. The study further incorporates lacunary refinements, enhancing the understanding of Nörlund statistical convergence and its symmetric properties. Key theorems, properties, and illustrative examples validate the proposed concepts, providing fresh insights into the role of symmetry in shaping broader convergence theories and advancing the understanding of sequence behavior across diverse mathematical frameworks.

Original languageEnglish
Article number192
JournalSymmetry
Volume17
Issue number2
DOIs
StatePublished - Feb 2025

Bibliographical note

Publisher Copyright:
© 2025 by the authors.

Keywords

  • deferred Nörlund lacunary density
  • deferred Nörlund lacunary statistical convergence
  • statistical convergence
  • strong deferred Nörlund lacunary summability

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