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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
We also analyze how to retrieve weightable quasi-metrics from real-valued functions satisfying suitable functional equations.
📌 3 Key Takeaways
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Objective & Hypothesis:Starting from the definition of a weightable quasi-metric we observe that several functional equations are induced in a natural way.
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Key Findings & Data:Studying these equations we characterize weightable quasi-metrics and show that they define representable total preorders.
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Conclusion & Impact:We also analyze how to retrieve weightable quasi-metrics from real-valued functions satisfying suitable functional equations.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Functional equations in two variables · Weightable quasi-metrics · Representable total preorders
Abstract
Starting from the definition of a weightable quasi-metric we observe that several functional equations are induced in a natural way. Studying these equations we characterize weightable quasi-metrics and show that they define representable total preorders. We also analyze how to retrieve weightable quasi-metrics from real-valued functions satisfying suitable functional equations.
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Cite This Article
Campion, M., Indurain, E., Ochoa, G., Valero, O. (2015). Functional equations related to weightable quasi-metrics. Hacettepe Journal of Mathematics and Statistics, Volume: 44 Issue: 4. https://ajindex.com/articles/1403257