...
首页> 外文期刊>Microwaves, Antennas & Propagation, IET >Design of an aperture-coupled microstrip antenna using a hybrid neural network
【24h】

Design of an aperture-coupled microstrip antenna using a hybrid neural network

机译:基于混合神经网络的孔径耦合微带天线设计

获取原文
获取原文并翻译 | 示例
           

摘要

In this study, an artificial neural network (ANN) model using hybrid neural network is proposed for the design of aperture-coupled microstrip antennas (ACMSAs). The new hybrid model is developed by combining radial basis function (RBF) and back-propagation algorithm (BPA). The performances evaluation of the hybrid model reveals superiority over the conventional BPA and RBF models in terms of error and time. The results obtained by the proposed model are compared with the simulation results obtained from the IE3D software package and also with the experimental results obtained from the fabricated ACMSA. The results show good agreement.
机译:在这项研究中,提出了一种使用混合神经网络的人工神经网络(ANN)模型来设计孔径耦合微带天线(ACMSA)。通过结合径向基函数(RBF)和反向传播算法(BPA)开发了新的混合模型。混合模型的性能评估显示出在误差和时间方面优于常规BPA和RBF模型。通过提议的模型获得的结果与从IE3D软件包获得的仿真结果以及从制造的ACMSA获得的实验结果进行了比较。结果显示出良好的一致性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号