Yang, J;
Tong, KF;
(2022)
Surface Wave Antenna Metallic Cell Pattern Design Using Neural Network Method.
In:
2022 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2022.
(pp. pp. 71-72).
IEEE: Narashino, Japan.
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Abstract
This work presents a surface wave antenna metallic cell pattern prediction method which can be generated based on the required far-field radiation pattern by the mean of applying Wasserstein generative adversarial network (WGAN) and bi-directional gated recurrent unit (Bi-GRU) neural network models. The predicted metallic cell pattern has been 3D-modelled in CST and the radiation pattern shows less than 1 dBi variation level from the desired input radiation pattern.
| Type: | Proceedings paper |
|---|---|
| Title: | Surface Wave Antenna Metallic Cell Pattern Design Using Neural Network Method |
| Event: | 2022 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM) |
| Dates: | 29 Aug 2022 - 31 Aug 2022 |
| ISBN-13: | 9781665432382 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/iWEM52897.2022.9993476 |
| Publisher version: | https://doi.org/10.1109/iWEM52897.2022.9993476 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10164348 |
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