Improving Generative Inverse Design of Rectangular Patch Antennas with Test Time Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909624039374848 |
|---|---|
| author | LaBash, Beck Khushrushahi, Shahriar Ruehle, Fabian |
| author_facet | LaBash, Beck Khushrushahi, Shahriar Ruehle, Fabian |
| contents | We propose a two-stage deep learning framework for the inverse design of rectangular patch antennas. Our approach leverages generative modeling to learn a latent representation of antenna frequency response curves and conditions a subsequent generative model on these responses to produce feasible antenna geometries. We further demonstrate that leveraging search and optimization techniques at test-time improves the accuracy of the generated designs and enables consideration of auxiliary objectives such as manufacturability. Our approach generalizes naturally to different design criteria, and can be easily adapted to more complex geometric design spaces. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_18188 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Improving Generative Inverse Design of Rectangular Patch Antennas with Test Time Optimization LaBash, Beck Khushrushahi, Shahriar Ruehle, Fabian Signal Processing Artificial Intelligence Machine Learning Systems and Control We propose a two-stage deep learning framework for the inverse design of rectangular patch antennas. Our approach leverages generative modeling to learn a latent representation of antenna frequency response curves and conditions a subsequent generative model on these responses to produce feasible antenna geometries. We further demonstrate that leveraging search and optimization techniques at test-time improves the accuracy of the generated designs and enables consideration of auxiliary objectives such as manufacturability. Our approach generalizes naturally to different design criteria, and can be easily adapted to more complex geometric design spaces. |
| title | Improving Generative Inverse Design of Rectangular Patch Antennas with Test Time Optimization |
| topic | Signal Processing Artificial Intelligence Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2505.18188 |