Probabilistic Generative Approach for Ambiguity-Aware Parameter Extraction

Artificial neural networks (ANNs) are increasingly used for parameter extraction in semiconductor device modeling. However, in practice, a parameter ambiguity issue arises, where multiple parameter combinations produce identical drain current values (<inline-formula> <tex-math notation=&quo...

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Bibliographic Details
Published in:	IEEE transactions on electron devices Vol. 72; no. 10; pp. 5544 - 5550
Main Authors:	Zeng, Bolun, Tang, Zhenhua, Zhang, Yuanke, Li, Qingsong, Zhou, Changchun, Qiu, Liling, Chen, Yuefeng, Xiang, Zikun, Xu, Jun, Luo, Chao, Guo, Guoping
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.10.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Ambiguity Artificial neural network (ANN) Artificial neural networks conditional variational autoencoder (CVAE) Decoding Gaussian distribution Integrated circuit modeling Mathematical models Optimization parameter ambiguity Parameter extraction Parameters Probabilistic logic Residual neural networks Semiconductor device modeling Semiconductor devices Threshold voltage Training
ISSN:	0018-9383, 1557-9646
Online Access:	Get full text
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