The Explosion of Artificial Intelligence in Antennas and Propagation: How Deep Learning Is Advancing Our State of the Art

Sawyer D. Campbell; Ronald P. Jenkins; Philip J. O'Connor; Douglas Werner

doi:10.1109/MAP.2020.3021433

The Explosion of Artificial Intelligence in Antennas and Propagation: How Deep Learning Is Advancing Our State of the Art

Sawyer D. Campbell, Ronald P. Jenkins, Philip J. O'Connor, Douglas Werner

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

The rise and proliferation of artificial intelligence (AI) has the potential to influence and disrupt many aspects of society, including antennas and propagation. This article provides information about he current state of the art (SOA) on applications of deep learning (DL) in problems of interest to the IEEE Antennas and Propagation Society (AP-S) community. A number of resources are provided to assist researchers to start using DL in their own research. Researchers also provide an outlook on DL’s potential impact on the AP-S as well as how exciting new hardware advancements may lead to significant improvements in the way we currently perform computational electromagnetic (CEM) simulations.

Original language	English (US)
Article number	9211490
Pages (from-to)	16-27
Number of pages	12
Journal	IEEE Antennas and Propagation Magazine
Volume	63
Issue number	3
DOIs	https://doi.org/10.1109/MAP.2020.3021433
State	Published - Jun 2021

All Science Journal Classification (ASJC) codes

Condensed Matter Physics
Electrical and Electronic Engineering

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10.1109/MAP.2020.3021433

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The Explosion of Artificial Intelligence in Antennas and Propagation: How Deep Learning Is Advancing Our State of the Art

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