Symbolic Regression Based on Kolmogorov–Arnold Networks for Gray-Box Simulation Program with Integrated Circuit Emphasis Model of Generic Transistors

In this paper, a novel approach to symbolic regression using Kolmogorov–Arnold Networks (KAN) for developing gray-box Simulation Program with Integrated Circuit Emphasis models of generic transistors is proposed. Unlike traditional black-box models, such as artificial neural networks, (ANN), the dev...

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Veröffentlicht in:	Electronics (Basel) Jg. 14; H. 6; S. 1161
Hauptverfasser:	Huang, Yiming, Li, Bin, Wu, Zhaohui, Liu, Wenchao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 16.03.2025
Schlagworte:	Accuracy Artificial neural networks Current voltage characteristics Datasets Design optimization Efficiency Formulas (mathematics) Integrated circuits Modelling Neural networks Product development Semiconductor chips Simulation Simulation methods Transistors
ISSN:	2079-9292, 2079-9292
Online-Zugang:	Volltext
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