Machine Learning in Electromagnetics: A Review and Some Perspectives for Future Research

Erricolo, Danilo; Chen, Pai-Yen; Rozhkova, Anastasiia; Torabi, Elahesadat; Bagci, Hakan; Shamim, Atif; Zhang, Xianglian

doi:10.25417/uic.12404360.v1

Machine Learning in Electromagnetics: A Review and Some Perspectives for Future Research

conference contribution

posted on 2020-06-18, 01:00 authored by Danilo ErricoloDanilo Erricolo, Pai-Yen Chen, Anastasiia Rozhkova, Elahesadat Torabi, Hakan Bagci, Atif Shamim, Xianglian Zhang

We review machine learning and its applications in
a wide range of electromagnetic problems, including radar,
communication, imaging and sensing. We extensively discuss some recent progress in development and use of intelligent algorithms for antenna design, synthesis, and characterization. We also provide some perspectives for future research directions in this emerging field of study.

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Danilo Erricolo, Pai-Yen Chen, Anastasiia Rozhkova, Elahesadat Torabi, Hakan Bagci, Atif Shamim, Xiangliang Zhang, “Machine Learning in Electromagnetics: A review and some perspectives for future research,” International Conference on Electromagnetics in Advanced Applications (ICEAA 2019), Granada, Spain, Sep. 9-13, 2019.

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IEEE

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en_US

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978-1-7281-0563-5, 978-1-7281-0562-8, 978-1-7281-0564-2

Issue date

2019-10-24

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Keywords—Electromagnetics, Artificial Neural Network, Machine Learning, Deep Learning Electrical and Electronic Engineering not elsewhere classified

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Machine Learning in Electromagnetics: A Review and Some Perspectives for Future Research

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