Neural network for the quantum correction of nanoscale SOI mosfets / 西安交通大学学报·英文版
Academic Journal of Xi'
;
an Jiaotong University;(4): 118-121, 2006.
Artigo
em Chinês
| WPRIM
| ID: wpr-844894
ABSTRACT
The quantum effect of carrier distribution in nanoscale SOI MOSFETs is evident and must be taken into consideration in device modeling and simulation. In this paper, a backpropagation neural network was applied to predict the quantum density of carriers from the classical density, and the influence of the network structure on training speed and accuracy was studied. It was concluded that a carefully trained neural network with two hidden layers using the Levenberg-Marquardt learning algorithm could predict the carrier quantum density of SOI MOSFETs in very good agreement with Schrödinger Poisson equations.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Tipo de estudo:
Estudo prognóstico
Idioma:
Chinês
Revista:
Academic Journal of Xi'an Jiaotong University
Ano de publicação:
2006
Tipo de documento:
Artigo
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