A simple patch antenna design library

A machine learning approach to the inverse design of microstrip patch antennas by predicting optimal physical dimensions from desired performance metrics.

Design of folded patch. Wireless Electromagnetic Technologies - University of Rome Tor Vergata

MATLAB Codes to design the parameters for a patch antenna

Design files for the S-band patch antenna to be on-board the AcubeSAT nanosatellite

Physics-constrained deep learning framework for real-time inverse design of patch antennas. Achieves sub-millimeter accuracy and 20x faster predictions than traditional EM simulations. Includes beginner-friendly Google Colab demo.

CST simulation of a 33 GHz microstrip patch antenna for breast cancer detection, analyzing return loss, gain, and radiation pattern for biomedical tissue interaction.

Patch Antenna module focuses on simplifying the automation of the design and optimization of PCB microstrip patch antennas. It handles the automation of calculations, openEMS simulation, and the subsequent optimization.

🛰️ Streamline antenna design with a physics-constrained deep learning framework for rapid and accurate patch antenna optimization.