Journals / Istanbul University Journal of Electrical and Electronics Engineering / 2001 / Cilt: 1 - Sayı: 2

Neuron models with voltage sources for cellular neural networks

Hücresel sinir ağları için gerilim kaynaklı hücre modelleri

Pages
209–221
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

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

The advantages and drawbacks of the proposed model is discussed in the conclusion section.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this paper, a novel Cellular Neural Network cell circuit based on independent and dependent voltage sources is proposed.
📊
Key Findings & Data:The equilibrium points for the cells are not the functions of Rx and Cx at the dynamic unit in this model unlike the conventional CNN circuit of Chua and Yang based on current sources.
💡
Conclusion & Impact:The advantages and drawbacks of the proposed model is discussed in the conclusion section.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this paper, a novel Cellular Neural Network cell circuit based on independent and dependent voltage sources is proposed. The equilibrium points for the cells are not the functions of Rx and Cx at the dynamic unit in this model unlike the conventional CNN circuit of Chua and Yang based on current sources. A complete cell circuit is designed and simulations for stable and astable cases are carried out. The advantages and drawbacks of the proposed model is discussed in the conclusion section.

Özet

Bu makalede, bağımsız ve bağımlı gerilim kaynağı tabanlı yeni bir Hücresel Sinir Ağı hücre devresi önerilmiştir. Bu modelde akım kaynaklı Chua ve Yang ‘ın klasik hücre devresinin aksine hücreler için denge noktaları dinamik birimdeki Rx ve Cx’ den bağımsızdırlar. Tam bir hücre devresi tasarlanıp kararlı ve kararsız durumlar için benzetimleri yapılmıstır. Önerilen modelin avantaj ve dezavantajları sonuçlar bölümünde tartışılmıştır.

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Cite This Article

TANDER, B., ÜN, M. (2022). Neuron models with voltage sources for cellular neural networks. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 1 - Sayı: 2, 209–221. https://ajindex.com/articles/543972

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References (10)

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