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

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