Fast impedance prediction for power distribution network using deep learning

Author:

Zhang Ling12,Juang Jack2,Kiguradze Zurab2,Pu Bo2,Jin Shuai3,Wu Songping3,Yang Zhiping3,Fan Jun2,Hwang Chulsoon2

Affiliation:

1. College of Information Science and Electronic Engineering Zhejiang University Hangzhou China

2. EMC Laboratory, Electrical and Computer Engineering Missouri University of Science and Technology Rolla Missouri USA

3. Google Inc. Mountain View California USA

Funder

National Science Foundation of Sri Lanka

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fast Decoupling Capacitor Optimization for Power Delivery Network Based on Model and Data Fusion Method;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19

2. 3D-IC Power Distribution Network (PDN) Impedance Prediction using Deep Learning (DL);2023 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS);2023-12-12

3. Generating AI modules for decoupling capacitor placement using simulation;Advances in Radio Science;2023-12-01

4. Machine Learning in Integrated Circuit Substrate Electrical Test (IMPACT 2023);2023 18th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT);2023-10-25

5. Decoupling Optimization for Complex PDN Structures Using Deep Reinforcement Learning;IEEE Transactions on Microwave Theory and Techniques;2023-09

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