Physics-Informed Neural Network for High Frequency Noise Performance in Quasi-Ballistic MOSFETs

Physics-Informed Neural Network for High Frequency Noise Performance in Quasi-Ballistic MOSFETs

A physics-informed neural network (PINN) model is presented to predict the nonlinear characteristics of high frequency (HF) noise performance in quasi-ballistic MOSFETs. The PINN model is formulated by combining the radial basis function-artificial neural networks (RBF-ANNs) with an improved noise e...

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Bibliographic Details
Main Author: Jonghwan Lee
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Electronics
Subjects:
physics-informed neural network
high frequency noise
quasi-ballistic MOSFETs
radial basis function-artificial neural network
tunneling current
thermal channel noise
Online Access:https://www.mdpi.com/2079-9292/10/18/2219

Internet

https://www.mdpi.com/2079-9292/10/18/2219

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