基于神经网络的超陡亚阈边坡装置建模

2022 IEEE International Meeting for Future of Electron Devices, Kansai (IMFEDK) Pub Date : 2022-11-28 DOI:10.1109/IMFEDK56875.2022.9975367

K. Nakata, Takayuki Mori, J. Ida

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引用次数: 0

摘要

本文采用神经网络对具有超陡亚阈值斜率(小于10 mV/dec)特性的pn -体束缚硅绝缘子场效应晶体管进行了特性建模。我们发现需要四个或更多的隐藏层来表达超陡的SS。

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Modeling of Super Steep Subthreshold Slope Device by using Neural Network

In this study, the characteristics modeling of a PN-body tied silicon on insulator field-effect transistor, which has super steep subthreshold slope (SS) (less than 10 mV/dec) characteristics, was tried by using a neural network. We found that four or more hidden layers are needed to express the super steep SS.

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2022 IEEE International Meeting for Future of Electron Devices, Kansai (IMFEDK)

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