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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
After that, we define the fuzzy conditional entropy function on (X, F, $mu$).Lastly, we investigate some important properties of this function.
📌 3 Key Takeaways
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Objective & Hypothesis:In this work, we first recall some basic properties of the soft fuzzy probability measure space (X, F, $mu$) without going into details.
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Key Findings & Data:In this work, we first recall some basic properties of the soft fuzzy probability measure space (X, F, $mu$) without going into details.
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Conclusion & Impact:After that, we define the fuzzy conditional entropy function on (X, F, $mu$).Lastly, we investigate some important properties of this function.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In this work, we first recall some basic properties of the soft fuzzy probability measure space (X, F, $mu$) without going into details. After that, we define the fuzzy conditional entropy function on (X, F, $mu$).Lastly, we investigate some important properties of this function.
Özet
Bu çalışmada ilk olarak detaya girilmeksizin, (X, F, $mu$) soft fuzzy olasılık ölçüm uzayının bazı temel özellikleri hatırlatıyor. Sonra (X, F, $mu$) üzerinde fuzzy koşullu eniropi fonksiyonu tanımlanıyor. Son olarak da bu fonksiyonun bazı önemli özellikleri inceleniyor.
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Cite This Article
TOK, İ. (2022). Fuzzy koşullu entropi fonksiyonu üzerine. Ege Üniversitesi Fen Fakültesi Dergisi Seri A - B, Cilt: 19 - Sayı: 1, 64–73. https://ajindex.com/articles/496336