Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning

Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning

In this work, a computationally efficient method based on data-driven surrogate models is proposed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a module that simultaneously pre-filters unwanted signals, and enhanc...

Full description

Bibliographic Details
Main Authors: Peyman Mahouti, Aysu Belen, Ozlem Tari, Mehmet Ali Belen, Serdal Karahan, Slawomir Koziel
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Electronics
Subjects:
metamaterials
optimization
deep learning
frequency selective surfaces
filtering antenna
Online Access:https://www.mdpi.com/2079-9292/12/7/1584

Internet

https://www.mdpi.com/2079-9292/12/7/1584

Similar Items