Device Modeling Based on Cost-Sensitive Densely Connected Deep Neural Networks
Engineers used TCAD tools for semiconductor devices modeling. However, it is computationally expensive and time-consuming for advanced devices with smaller dimensions. Therefore, this work proposes a machine learning-based device modeling algorithm to capture the complex nonlinear relationship betwe...
Saved in:
Main Authors: | Xiaoying Tang, Zhiqiang Li, Lang Zeng, Hongwei Zhou, Xiaoxu Cheng, Zhenjie Yao |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Journal of the Electron Devices Society |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10643157/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Nudibranch Suborders Classification based on Densely Connected Convolutional Networks
by: Timothy Christyan, et al.
Published: (2024-03-01) -
Estimating Aggregate Capacity of Connected DERs and Forecasting Feeder Power Flow With Limited Data Availability
by: Amir Reza Nikzad, et al.
Published: (2024-01-01) -
Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection
by: Manh-Tuan Do, et al.
Published: (2025-01-01) -
Prediction of viscosity of blast furnace slag based on NRBO-DNN model
by: Zhe Li, et al.
Published: (2025-04-01) -
The Influence of Political Connections on the Cost of Capital and the Performance of Companies Listed on B3
by: Jaison Caetano da Silva, et al.
Published: (2018-01-01)