Title :
Modeling ballistic double gate MOSFETs using neural networks approach
Author :
Abo-Elhadeed, Ahmed F.
Author_Institution :
Device Modeling Team, Mentor Graphics, Cairo, Egypt
Abstract :
This paper presents modeling ballistic double gate MOSFETs by a neural network approach. A complete neural network structure is proposed to model the double gate characteristics. To confirm the accuracy of the proposed network, the drain current characteristics are compared to the nanoMOS device simulator data. The comparison shows excellent agreements with percentage errors lower than 1% over a range of drain and gate voltages as well as channel lengths and silicon thicknesses.
Keywords :
MOSFET; neural nets; ballistic double gate MOSFET; drain current characteristics; gate voltage; nanoMOS device simulator data; neural network structure; silicon thickness; Artificial neural networks; Integrated circuit modeling; Logic gates; MOSFETs; Mathematical model; Silicon; Training; ballistic; double gate; modeling; neural networks;
Conference_Titel :
Electron Devices (CDE), 2011 Spanish Conference on
Conference_Location :
Palma de Mallorca
Print_ISBN :
978-1-4244-7863-7
DOI :
10.1109/SCED.2011.5744165
