Sequential Policy Network-based Optimal Passive Equalizer Design for an Arbitrary Channel of High Bandwidth Memory using Advantage Actor Critic

Author:

Choi Seonguk,Kim Minsu,Park Hyunwook,Son Keeyoung,Kim Seongguk,Kim Jihun,Park Joonsang,Kim Haeyeon,Shin Taein,Kim Keunwoo,Kim Joungho

Funder

National Research Foundation of Korea

Publisher

IEEE

Cited by 6 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. Utilizing Deep Reinforcement Learning for High-Voltage Distribution Network Expansion Planning;2024 IEEE 2nd International Conference on Power Science and Technology (ICPST);2024-05-09

2. Imitation Learning-based Equalizer Design Optimization Method on PCIe 6.0;2023 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS);2023-12-12

3. Bayesian Exploration Imitation Learning-Based Contextual via Design Optimization Method of PAM-4-Based High-Speed Serial Link;IEEE Transactions on Electromagnetic Compatibility;2023-12

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. Adaptive Gramian-Angular-Field Segmentation Integration Based Generative Adversarial Network (AGSI-GAN) for Eye Diagram Estimation of High Bandwidth Memory (HBM) Interposer;2023 IEEE 32nd Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS);2023-10-15

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