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Erschienen in:
07.08.2019
Attenuation constant and characteristic impedance calculation of top metal-covered CPW transmission line using neural networks
Erschienen in: Journal of Computational Electronics | Ausgabe 4/2019
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Abstract
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 µm. 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.