Search
Numerical and experimental generated data during project https://doi.org/10.3390/electronics12163462
Description
The dataset was generated using a procedure for unsupervised specification-driven design of planar antennas. The presented methodology capitalizes on a flexible and scalable antenna parameterization, which enables the realization of complex geometries while maintaining reasonably small parameter space dimensionality. A customized nature-inspired algorithm is employed to carry out space exploration and identification of a quasi-optimum antenna topology in a global sense. A fast gradient-based procedure is then incorporated to fine-tune antenna dimensions. The design framework works entirely in a black-box fashion with the only input being design specifications, and optional constraints, e.g., concerning the structure size. Numerous illustration case studies demonstrate the capability of the presented technique to generate unconventional antenna topologies of satisfactory performance using reasonable computational budgets and with no human expert interaction necessary whatsoever.
Dataset file
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.Example script for calculation:
https://github.com/antespi/s3md5
File details
- License:
-
open in new tab
CC BYAttribution
Details
- Year of publication:
- 2025
- Verification date:
- 2025-03-17
- Dataset language:
- English
- DOI:
- DOI ID 10.34808/hn5w-wa16 open in new tab
- Funding:
- Verified by:
- Gdańsk University of Technology
Keywords
- antenna design
- unsupervised design
- artificial intelligence
- design automation
- nature-inspired optimization
References
- publication On Unsupervised Artificial-Intelligence-Assisted Design of Antennas for High-Performance Planar Devices
Cite as
Authors
seen 11 times