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首页> 外文期刊>Journal of Computational Electronics >Attenuation constant and characteristic impedance calculation of top metal-covered CPW transmission line using neural networks
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Attenuation constant and characteristic impedance calculation of top metal-covered CPW transmission line using neural networks

机译:基于神经网络的顶部金属包覆CPW传输线的衰减常数和特征阻抗计算

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摘要

A technique for calculating the characteristic impedance of top metal-covered coplanar waveguide (TCPW) transmission lines using a neural network is presented in this paper. Additionally, the technique is extended to calculate their attenuation constant. Analytical expressions based on conformal mapping techniques are not applicable when the top cover height is <3 mu m. Further, there are no analytical expressions available to calculate their attenuation constant. We used a feed-forward artificial neural network to calculate the characteristic impedance and attenuation constant of TCPWs. The results are compared with those obtained using ANSYS HFSS full-wave simulation software, which shows good agreement. This technique will be useful for equivalent circuit modeling of RF-MEMS.
机译:本文提出了一种使用神经网络计算覆盖金属的共面波导(TCPW)传输线的特征阻抗的技术。另外,扩展了该技术以计算其衰减常数。当顶盖高度小于3微米时,基于共形映射技术的分析表达式不适用。此外,没有解析表达式可用于计算其衰减常数。我们使用前馈人工神经网络来计算TCPW的特征阻抗和衰减常数。将结果与使用ANSYS HFSS全波仿真软件获得的结果进行了比较,结果显示出良好的一致性。该技术将对RF-MEMS的等效电路建模有用。

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