Deep learning-based fast BSIM-CMG parameter extraction for general input dataset
A deep learning (DL) technique to extract the set of Berkeley short-channel IGFET model-
common multigate (BSIM-CMG) compact model parameters directly from experimental …
common multigate (BSIM-CMG) compact model parameters directly from experimental …
Device Modeling Based on Cost-Sensitive Densely Connected Deep Neural Networks
X Tang, Z Li, L Zeng, H Zhou… - IEEE Journal of the …, 2024 - ieeexplore.ieee.org
Engineers used TCAD tools for semiconductor devices modeling. However, it is
computationally expensive and time-consuming for advanced devices with smaller …
computationally expensive and time-consuming for advanced devices with smaller …
DrPCE-Net: Differential Residual PCE Network for Characteristic Prediction of Transistors
Data-driven machine learning (ML) has emer-ged as an effective approach to providing
insights into transistor devices prior to manufacture. Despite its success, most ML methods …
insights into transistor devices prior to manufacture. Despite its success, most ML methods …
Enhancement and Expansion of the Neural Network-Based Compact Model Using a Binning Method
The artificial neural network (ANN)-based compact model has significant advantages over
physics-based standard compact models such as BSIM-CMG because it can achieve higher …
physics-based standard compact models such as BSIM-CMG because it can achieve higher …
Benchmarking artificial neural network models for design technology co-optimization
Device modeling with artificial neural networks (ANN) has been explored in the community.
However, figure of merits of ANN models in application scenarios have not been fully …
However, figure of merits of ANN models in application scenarios have not been fully …
Compact Modeling of N-and P-Type GAA NS FETs Using Physical-Based Artificial Neural Networks with Temperature Dependence
Y Dei, YS Yang, Y Li - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
We propose a compact model that utilizes physical-based artificial neural networks (ANNs)
to model the effect of temperature on n-and p-type gate-all-around nanosheet FETs. Our …
to model the effect of temperature on n-and p-type gate-all-around nanosheet FETs. Our …