利用深度学习和人工智能设计射频滤波器

2022 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO) Pub Date : 2022-07-06 DOI:10.1109/NEMO51452.2022.10038522

Mouatez Bellah Karabaghli, K. Frigui, Mouhamadou Moctar, S. Bila, D. Baillargeat

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摘要

本文提出了一种基于深度学习的射频滤波器优化方法。这种方法可以基于s参数作为输入数据来预测RF滤波器的几何尺寸。通过设计一个四极矩形波导滤波器，详细验证了该方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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RF filter design using Deep Learning and Artificial Intelligence

In this paper an RF filter optimization by using deep learning method is presented. This approach allows to predict the geometrical dimensions of the RF filter based on S-parameters as input data. A validation of this method is detailed by designing a four-pole rectangular waveguide filter.

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2022 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO)

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