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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
By utilizing these non-topological concepts, we derive some new results pertaining to these operators.
📌 3 Key Takeaways
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Objective & Hypothesis:This research paper introduces and establishes the concept of compact operators in the context of Riesz spaces, specifically considering statistical order convergence.
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Key Findings & Data:We define statistical order compact operators as operators that map statistical order bounded sequences to sequences with statistical order convergent subsequences.
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Conclusion & Impact:By utilizing these non-topological concepts, we derive some new results pertaining to these operators.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:compact operator · Riesz space · statistical order convergence
Abstract
This research paper introduces and establishes the concept of compact operators in the context of Riesz spaces, specifically considering statistical order convergence. We define statistical order compact operators as operators that map statistical order bounded sequences to sequences with statistical order convergent subsequences. Additionally, we define statistical $M$-weakly compact operators. By utilizing these non-topological concepts, we derive some new results pertaining to these operators.
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Cite This Article
Aydın, A. (2024). Statistically order compact operators on Riesz spaces. Hacettepe Journal of Mathematics and Statistics, Volume: 53 Issue: 3. https://doi.org/10.15672/hujms.1223922