Improvement of TCAD Augmented Machine Learning Using Autoencoder for Semiconductor Variation Identification and Inverse Design

Improvement of TCAD Augmented Machine Learning Using Autoencoder for Semiconductor Variation Identification and Inverse Design

A machine learning (ML) model by combing two autoencoders and one linear regression model is proposed to avoid overfitting and to improve the accuracy of Technology Computer-Aided Design (TCAD)-augmented ML for semiconductor structural variation identification and inverse design, without using domai...

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Bibliographic Details
Main Authors: Kashyap Mehta, Sophia Susan Raju, Ming Xiao, Boyan Wang, Yuhao Zhang, Hiu Yung Wong
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Autoencoder
defect identification
inverse design
machine learning
TCAD simulation
variability
Online Access:https://ieeexplore.ieee.org/document/9159651/

Internet

https://ieeexplore.ieee.org/document/9159651/

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