Data Driven Surrogate Modeling of Phase Array Antennas Using Deep Learning for Millimetric Band Applications

Phased Array Antenna (PAA) technology plays an important role in fields such as radar, 5G and satellite or any application which requires wide bandwidth and high gain. However, achieving such design is a difficult and complex task that requires an accurate calculation and combination of results obta...

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Bibliographic Details
Published in:	IEEE access Vol. 11; pp. 114415 - 114423
Main Authors:	Tulum, Mehmet Akif, Turk, Ahmet Serdar, Mahouti, Peyman
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Antenna arrays Antennas Artificial intelligence Broadband Broadband antennas Computational efficiency Computational electromagnetics Computational modeling Computing costs Computing time data driven modelling Data models Deep learning High gain Machine learning Modelling Optimization phased array antenna Phased arrays Prediction models Radar antennas Simulation surrogate modelling
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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