UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Metallic Pattern Prediction for Surface Wave Antennas Using Bidirectional Gated Recurrent Unit Neural Network

Yang, J; Tong, KF; (2021) Metallic Pattern Prediction for Surface Wave Antennas Using Bidirectional Gated Recurrent Unit Neural Network. Presented at: 2021 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), Honolulu, HI, USA. Green open access

[thumbnail of ICEAA_ExtendedAbstract.pdf]
Preview
Text
ICEAA_ExtendedAbstract.pdf - Accepted version

Download (242kB) | Preview

Abstract

This work presents a surface wave antenna metallic pattern prediction from electric field in near-field by applying Bidirectional Gated Recurrent Unit neural network prediction model. The metallic pattern of the proposed antenna has been predicted by using Bi-GRU neural network model with prediction accuracy 100% at 34.5GHz. Different uniform mark-space-ratios (MSR) of the metallic pattern do not affect the metallic pattern prediction accuracy.

Type: Conference item (Presentation)
Title: Metallic Pattern Prediction for Surface Wave Antennas Using Bidirectional Gated Recurrent Unit Neural Network
Event: 2021 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC)
Location: Honolulu, HI, USA
Dates: 9-13 Aug 2021
ISBN-13: 9781665413886
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/APWC52648.2021.9539634
Publisher version: http://dx.doi.org/10.1109/APWC52648.2021.9539634
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/10139114
Downloads since deposit
3Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item