Open AccessDouble Gate MOSFET Modeling Based on Adaptive Neuro‐Fuzzy Inference System for Nanoscale Circuit Simulation
Author(s) -
Hayati Mohsen,
Seifi id,
Rezaei Abbas
Publication year - 2010
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.10.0109.0707
Subject(s) - adaptive neuro fuzzy inference system , mosfet , electronic engineering , field effect transistor , electronic circuit simulation , scaling , electronic circuit , quantum , transistor , neuro fuzzy , computer science , fuzzy logic , engineering , physics , electrical engineering , artificial intelligence , mathematics , fuzzy control system , voltage , quantum mechanics , geometry
As the conventional silicon metal‐oxide‐semiconductor field‐effect transistor (MOSFET) approaches its scaling limits, quantum mechanical effects are expected to become more and more important. Accurate quantum transport simulators are required to explore the essential device physics as a design aid. However, because of the complexity of the analysis, it has been necessary to simulate the quantum mechanical model with high speed and accuracy. In this paper, the modeling of double gate MOSFET based on an adaptive neuro‐fuzzy inference system (ANFIS) is presented. The ANFIS model reduces the computational time while keeping the accuracy of physics‐based models, like non‐equilibrium Green's function formalism. Finally, we import the ANFIS model into the circuit simulator software as a subcircuit. The results show that the compact model based on ANFIS is an efficient tool for the simulation of nanoscale circuits.