Decoupling Capacitor Selection Algorithm for PDN Based on Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Decoupling Capacitor Selection Algorithm for PDN Based on Deep Reinforcement Learning

Published:2019-07 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE International Symposium on Electromagnetic Compatibility, Signal & Power Integrity (EMC+SIPI)
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Author:

Zhang Ling,Zhang Zhongyang,Huang Chenxi,Deng Han,Lin Hank,Tseng Bin-Chyi,Drewniak James,Hwang Chulsoon

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8822234/8825188/08825249.pdf?arnumber=8825249

Cited by 22 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. A Novel Physics-Assisted Genetic Algorithm for Decoupling Capacitor Optimization;IEEE Transactions on Microwave Theory and Techniques;2024-08

2. Pin-Opt: Graph Representation Learning for Large-Scale Pin Assignment Optimization of Microbumps Considering Signal and Power Integrity;IEEE Transactions on Components, Packaging and Manufacturing Technology;2024-04

3. Decoupling Capacitor Optimization for 2.5D-ICs With Deep Reinforcement Learning Technique;2024 Conference of Science and Technology for Integrated Circuits (CSTIC);2024-03-17

4. Deep Reinforcement Learning-Based Optimal and Fast Hybrid Equalizer Design Method for High-Bandwidth Memory (HBM) Module;IEEE Transactions on Components, Packaging and Manufacturing Technology;2023-11

5. Prediction of automotive radiated emission using machine learning;2023 International Symposium on Electromagnetic Compatibility – EMC Europe;2023-09-04

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