Neuro-space mapping-based DC modeling for 130-nm MOSFET

Shoulin Li; Bo Han; Jiali Cheng; Jianjun Gao

doi:10.1002/mmce.20469

Neuro-space mapping-based DC modeling for 130-nm MOSFET

Shoulin Li^*
, Bo Han
, Jiali Cheng
, Jianjun Gao

^*Corresponding author for this work

School of Physics and Electronic Science

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

In this article, two approaches for modeling DC characteristics for MOSFET based on neuro-space mapping (SM) are proposed. The first approach makes use of classical neuro-SM technology, while the second combines neuro-SM with prior knowledge input and source difference method. The formulas for obtaining the transconductance and output conductance in two approaches are derived. The I ? V characteristics as well as their conductances obtained by the formulas in two approaches are compared to the measured data. Experimental results, which confirm the validity of our approaches, are also presented.

Original language	English
Pages (from-to)	587-592
Number of pages	6
Journal	International Journal of RF and Microwave Computer-Aided Engineering
Volume	20
Issue number	5
DOIs	https://doi.org/10.1002/mmce.20469
State	Published - Sep 2010

Keywords

MOSFET
device modeling
neural network
parameter extraction
space mapping

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10.1002/mmce.20469

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title = "Neuro-space mapping-based DC modeling for 130-nm MOSFET",

abstract = "In this article, two approaches for modeling DC characteristics for MOSFET based on neuro-space mapping (SM) are proposed. The first approach makes use of classical neuro-SM technology, while the second combines neuro-SM with prior knowledge input and source difference method. The formulas for obtaining the transconductance and output conductance in two approaches are derived. The I ? V characteristics as well as their conductances obtained by the formulas in two approaches are compared to the measured data. Experimental results, which confirm the validity of our approaches, are also presented.",

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AU - Li, Shoulin

AU - Han, Bo

AU - Cheng, Jiali

AU - Gao, Jianjun

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N2 - In this article, two approaches for modeling DC characteristics for MOSFET based on neuro-space mapping (SM) are proposed. The first approach makes use of classical neuro-SM technology, while the second combines neuro-SM with prior knowledge input and source difference method. The formulas for obtaining the transconductance and output conductance in two approaches are derived. The I ? V characteristics as well as their conductances obtained by the formulas in two approaches are compared to the measured data. Experimental results, which confirm the validity of our approaches, are also presented.

AB - In this article, two approaches for modeling DC characteristics for MOSFET based on neuro-space mapping (SM) are proposed. The first approach makes use of classical neuro-SM technology, while the second combines neuro-SM with prior knowledge input and source difference method. The formulas for obtaining the transconductance and output conductance in two approaches are derived. The I ? V characteristics as well as their conductances obtained by the formulas in two approaches are compared to the measured data. Experimental results, which confirm the validity of our approaches, are also presented.

KW - MOSFET

KW - device modeling

KW - neural network

KW - parameter extraction

KW - space mapping

UR - https://www.scopus.com/pages/publications/78649283637

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JF - International Journal of RF and Microwave Computer-Aided Engineering

IS - 5

ER -

Neuro-space mapping-based DC modeling for 130-nm MOSFET

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Keywords

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