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Analog Circuit Design Automation via Sequential RL Agents and Gm/ID Methodology

This paper studies the problem of designing analog circuits to achieve target specifications, which can be formulated as a multi-objective combinatorial optimization (MOCO) under uncertainty. We address this challenging problem using the <inline-formula> <tex-math notation="LaTeX">$g_{m} / I_{D}$ </...

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Автори: Sungweon Hong, Yunseob Tae, Dongjun Lee, Gijin Park, Jaemyung Lim, Kyungjun Cho, Chunseok Jeong, Myeong-Jae Park, Songnam Hong, Jaeduk Han
Формат: Artigo
Мова:Inglês
Опубліковано: IEEE 2024-01-01
Серія:IEEE Access
Предмети:
Analog circuits
automation of analog design
combinatorial optimization
gm/ID methodology
reinforcement learning
Онлайн доступ:https://ieeexplore.ieee.org/document/10614161/
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