Machine learning-based technique for gain and resonance prediction of mid band 5G Yagi antenna

• Main Authors: Haque, M.A., Rahman, M.A., Al-Bawri, S.S., Yusoff, Z., Sharker, A.H., Abdulkawi, W.M., Saha, D., Paul, L.C., Zakariya, M.A.
• Format: Article
• Published: Nature Research 2023
• Online Access: http://scholars.utp.edu.my/id/eprint/37277/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166595533&doi=10.1038%2fs41598-023-39730-1&partnerID=40&md5=25f2fedeac46bc2fbd9d7b974e1f77c8

In this study, we present our findings from investigating the use of a machine learning (ML) technique to improve the performance of Quasi-Yagi�Uda antennas operating in the n78 band for 5G applications. This research study investigates several techniques, such as simulation, measurement, and an R...