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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
In this work we propose a modification of the learning algorithm of one of the first learning models, namely the perceptron model, to make it more consistent with real biological systems.
📌 3 Key Takeaways
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Objective & Hypothesis:In this work we propose a modification of the learning algorithm of one of the first learning models, namely the perceptron model, to make it more consistent with real biological systems.
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Key Findings & Data:In this work we propose a modification of the learning algorithm of one of the first learning models, namely the perceptron model, to make it more consistent with real biological systems.
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Conclusion & Impact:In this work we propose a modification of the learning algorithm of one of the first learning models, namely the perceptron model, to make it more consistent with real biological systems.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In this work we propose a modification of the learning algorithm of one of the first learning models, namely the perceptron model, to make it more consistent with real biological systems.
Özet
Bu çalışmada öğrenme modellerinin ilklerinden sayılan pörseptron modeli kısaca tanıtılıp, öğrenme algoritmasmda yapılan bir değişiklikle, pörseptron modelinin gerçek biyolojik sistemlere uygunluğu sağlanmaya çalışılmıştır.
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Cite This Article
MAHİR, N., DEMİR, B., ÇETİN, N. (2022). A modification of perceptron model. Anadolu Üniversitesi Fen Fakültesi Dergisi, Cilt: 0 - Sayı: 4, 65–72. https://ajindex.com/articles/438655