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

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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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Citation

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.

Publisher

IEEE

Language

  • en_US

isbn

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

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

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    In Copyright

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