论文标题
基于剩余网络的直接合成EM结构：一对一变压器的研究
Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers
论文作者
论文摘要
我们建议使用机器学习模型直接合成芯片电磁（EM）被动结构，以实现快速甚至自动化的设计以及对RF/MM波电路的优化。作为概念证明，我们使用我们提出的神经网络模型在45nm SOI过程中直接综合了1：1变压器。该模型使用预先存在的变压器S参数文件及其几何设计培训样品，可预测目标几何设计。
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.
