吉林大学学报(工学版) ›› 2022, Vol. 52 ›› Issue (12): 3022-3028.doi: 10.13229/j.cnki.jdxbgxb20210440
You-jun ZHANG(),Shun-yan CHENG
摘要:
针对神经网络微波建模耗时难的问题,提出了一种基于卷积神经网络的微带滤波器结构参数估计方法。采用单开路短截线加载矩形环谐振器和横向信号干扰技术分析和设计了一款双频带、三频带和四频带的微带滤波器,并利用电磁仿真软件提取数据。将微带滤波器的S参数和结构参数分别作为模型的输入和输出进行训练,并通过训练好的模型进行结构参数预测。利用卷积神经网络设计微带滤波器的方法,能够有效解决目前基于神经网络设计微带滤波器时输入参数较多、全连接造成模型复杂以及耗时长等问题。仿真结果表明,该方法设计的微带滤波器S参数有较高的准确率。
中图分类号:
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