Machine learning-based technique for gain and resonance prediction of mid band 5G Yagi antenna
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...
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| 主要な著者: | , , , , , , , , |
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| フォーマット: | 論文 |
| 出版事項: |
Nature Research
2023
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| オンライン･アクセス: | 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 |
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