Journals / Electronic Letters on Science and Engineering / 2006 / Cilt: 2 - Sayı: 2

Mathematical Modelling of the Bipolar Transistor using Artificial Neural Networks

Yapay Sinir Aglari ile Bipolar Transistorun Matematiksel Modelinin Olusturulmasi

Pages
30–35
Publication Date
2006-08-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Here the approaches to realize the outlined requirements are summarized.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Requirements for circuit simulation are increasing according to the development of system integration with many different functions.
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Key Findings & Data:To assist the development, the most important modeling issue is to guarantee sufficient simulation accuracy and applicability for any advanced technology.
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Conclusion & Impact:Here the approaches to realize the outlined requirements are summarized.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:BJT transistor · Yapay Sinir Agi · BJT Transistor Matematiksel Model

Abstract

Requirements for circuit simulation are increasing according to the development of system integration with many different functions. To assist the development, the most important modeling issue is to guarantee sufficient simulation accuracy and applicability for any advanced technology. For achieving this task it is inevitable to maintain a physically correct modeling of the real technology processes which govern the function of these BJT’s, even in the circuit simulation model. Here the approaches to realize the outlined requirements are summarized.

Özet

Yapay Sinir Aglari (YSA), giris verilerinin yetersiz oldugu, mevcut verilerden hareketle bilinmeyen iliskilerin ortaya çikarilmasi ve algoritmasi veya kurallari tam olarak bilinmeyen durumlar için gelistirilmis bir bilgi isleme sistemidir. Bu çalismada, YSA mimarisi kullanilarak, bipolar transistorlara ait gerçek karakteristikler üzerinden belirlenen az sayida veriyle transistora iliskin matematiksel model olusturulmustur. BJT transistorlara ait geçis karakteristigi verileri giris vektörü olarak aga sunulmus ve YSA’nin egitim islemi bu karakteristikler üzerinden gerçeklestirilmistir. Egitiminin ardindan degisik transistorlara ait test girisleriyle YSA’nin ögrenme basarimi denenmis, degisik transistorlara ait modellerinin matematiksel olarak yüksek dogrulukta olusturuldugu gösterilmistir.

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Cite This Article

BARAKLI, B., YENER, S., ARSLAN, E. (2006). Mathematical Modelling of the Bipolar Transistor using Artificial Neural Networks. Electronic Letters on Science and Engineering, Cilt: 2 - Sayı: 2, 30–35. https://ajindex.com/articles/133687

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