원문정보
보안공학연구지원센터(IJHIT)
International Journal of Hybrid Information Technology
Vol.9 No.10
2016.10
pp.149-160
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this article, we modelled and simulated Carbon Nanotube Field Effect Transistors (CNTFET); this transistor has a carbon nanotube channel. An Artificial Neural Networks (ANN) model was developed to reproduce accurately the behavior of CNTFET to predict its response for a wide range of temperature and voltage with focusing on the experimental data. The neural model is tested and validated; hence the ANN model is able to predict the CNTFET behavior with good accuracy. Finally, the proposed ANN model is integrated as a component in the library of simulation software of PSPICE electronic components.
목차
Abstract
1. Introduction
2. Artificial Neural Networks (ANN)
3. C-CNTFET Modeling using Neural Networks
3.1. Implementation of the Model ANN on PSPICE
3.2. PSPICE Input / Output Signals of the ANN Model of Inverter
3.3. PSPICE Input and Output Signals of the Ring Oscillator ANN Model
4. Conclusion
References
1. Introduction
2. Artificial Neural Networks (ANN)
3. C-CNTFET Modeling using Neural Networks
3.1. Implementation of the Model ANN on PSPICE
3.2. PSPICE Input / Output Signals of the ANN Model of Inverter
3.3. PSPICE Input and Output Signals of the Ring Oscillator ANN Model
4. Conclusion
References
키워드
저자정보
참고문헌
자료제공 : 네이버학술정보