结合神经网络和传递函数的毫米波无源元件参数化建模

Venu-Madhav-Reddy Gongal-Reddy, F. Feng, Qi-jun Zhang
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引用次数: 13

摘要

本文提出将神经网络与传递函数相结合的方法用于毫米波无源器件的参数化建模。人工神经网络(ANN)技术被认为是模拟微波元件电磁行为的有力工具。在本文中,我们训练人工神经网络将几何变量映射到传递函数的系数上。该方法得到的模型精度较高,可进一步用于高层设计。用两个毫米波算例验证了该方法的有效性。
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Parametric modeling of millimeter-wave passive components using combined neural networks and transfer functions
This paper propose to develop the combined neural networks and transfer functions (neuro-TF) for parametric modeling of millimeter-wave passive components. Artificial neural networks (ANN) techniques are recognized as a powerful tool for modeling the EM behavior of microwave components. In this paper, we train the ANN to map geometrical variables onto coefficients of transfer functions. The model obtained using our proposed technique can achieve good accuracy, and can be further used in the high-level design. Two millimeter-wave examples are used to demonstrate the validity of this technique.
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