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arXiv · 2008.10755

Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers

David Munzer·Siawpeng Er·Minshuo Chen·Yan Li·Naga S. Mannem·Tuo Zhao·Hua Wang
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Abstract

We propose using machine learning models for the direct synthesis of on-chip electromagnetic (EM) passive structures to enable rapid or even automated designs and optimizations of RF/mm-Wave circuits. As a proof of concept, we demonstrate the direct synthesis of a 1:1 transformer on a 45nm SOI process using our proposed neural network model. Using pre-existing transformer s-parameter files and their geometric design training samples, the model predicts target geometric designs.

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David Munzer, Siawpeng Er, Minshuo Chen, Yan Li, Naga S. Mannem, Tuo Zhao, Hua Wang. 2020-08-25. Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers. https://arxiv.org/abs/2008.10755

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