Novel Target-Impedance Extraction Method-Based Optimal PDN Design for High-Performance SSD Using Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Novel Target-Impedance Extraction Method-Based Optimal PDN Design for High-Performance SSD Using Deep Reinforcement Learning

Published:2023 Issue: Volume:2 Page:1-12
ISSN:2768-1866
Container-title:IEEE Transactions on Signal and Power Integrity
language:
Short-container-title:IEEE Trans. Signal and Power Integr.

Author:

Song Jinwook¹^ORCID,Jung Daniel Hyunsuk¹^ORCID,Shin Jaeyoung¹,Ryu Chunghyun¹,Ko Youngjun¹,Jin Sungwoo¹,Jung Soyoung¹,Kim Kyungsuk¹,Ku Youngmin¹,Choi Jung-Hwan¹^ORCID,Chun Sunghoon¹,Park Jonggyu¹^ORCID

Affiliation:

1. Samsung Electronics, Hwaseong, South Korea

Funder

Special Section and is an expanded version from the 2021

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9745882/10040918/10015885.pdf?arnumber=10015885

Reference22 articles.

1. Reinforcement Learning-Based Decap Optimization Method for High-Performance Solid-State Drive

2. Decoupling capacitors selection algorithm based on maximum anti‐resonance points and quality factor of capacitor

3. Playing atari with deep reinforcement learning;mnih;Proc 27th Conf NIPS Deep Learn Workshop,0

4. Reinforcement Learning-Based Optimal on-Board Decoupling Capacitor Design Method

5. Chip-package hierarchical power distribution network modeling and analysis based on a segmentation method;kim;IEEE Trans Adv Packag,2010

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