Machine learning‐driven design of dual‐band antennas using PGGAN and enhanced feature mapping
Abstract This paper presents a systematic antenna design methodology that integrates machine learning, leveraging the progressive growth technique of Progressive Growing of GANs (PGGAN) to generate images of various dual‐band PIFA‐like antenna structures. The process involves using data augmentation...
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| Main Authors: | Lung‐Fai Tuen, Ching‐Lieh Li, Yu‐Jen Chi, Chien‐Ching Chiu, Po Hsiang Chen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-12-01
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| Series: | IET Microwaves, Antennas & Propagation |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/mia2.12534 |
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