基于人工神经网络的维瓦尔第天线曲线槽参数建模

Wen-Hao Su, Wei Shao, Haiyan Ou, Sheng-Jun Zhang
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引用次数: 0

摘要

本文针对维瓦尔第天线的曲线槽提出了一种基于参数建模的人工神经网络(ANN)模型。通过立方样条插值而不是金属贴片的图片,向 ANN 输入产生弯曲边缘的点位置,从而实现了更有效的处理方法。ANN 的预测结果(包括 S 参数和增益)与全波仿真结果非常吻合。利用训练好的模型,通过多目标遗传算法优化了具有较低截止频率的维瓦尔第天线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parametric Modeling for Curved Slots of Vivaldi Antenna Based on Artificial Neural Network
This paper proposes an artificial neural network (ANN) model based on parametric modeling for curved slots of the Vivaldi antenna. A more effective processing method is achieved by feeding ANN with the point positions that produce curved edges via cubic spline interpolation rather than the picture of metallic patches. The predicted results of ANN, including S-parameter and gain, agree well with those from the full-wave simulation. With the trained model, a Vivaldi antenna with the lower cut-off frequency is optimized by the multi-objective genetic algorithm.
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