Title :
Adaptive Neural Network Model for SOI-MOSFET I-V Characteristic Including Self-Heating Effect
Author :
Karami, Mohammad Azim ; Afzali-Kusha, Ali
Author_Institution :
Nanoelectron. Center of Excellence, Tehran Univ., Tehran
Abstract :
In this paper, a model for SOI MOSFETs which considers the self-heating effect is proposed. The model which is based on a multi layer perceptron (MLP) neural network, generates the drain current as a function of the gate-source voltage, drain-source voltage, and the device temperature. Based on the current, the temperature of the device channel is calculated. The neural network adapts itself with the channel temperature which can be calculated by an equivalent thermal model for the SOI device.
Keywords :
MOSFET; multilayer perceptrons; semiconductor device models; silicon-on-insulator; I-V characteristic; SOI MOSFET; Si; adaptive neural network model; channel temperature; device channel; device temperature; drain current; drain-source voltage; equivalent thermal model; gate-source voltage; multilayer perceptron neural network; self-heating effect; silicon on insulator; Adaptive systems; Electron mobility; Insulation; Integrated circuit reliability; MOSFETs; Nanoelectronics; Neural networks; Silicon on insulator technology; Temperature; Voltage; Neural networks; Self-heating; Silicon on insulator;
Conference_Titel :
Microelectronics, 2006. ICM '06. International Conference on
Conference_Location :
Dhahran
Print_ISBN :
1-4244-0764-8
Electronic_ISBN :
1-4244-0765-6
DOI :
10.1109/ICM.2006.373640
