Machine Learning in Electromagnetics: A Review and Some Perspectives for Future Research
Type
Conference PaperAuthors
Erricolo, DaniloChen, Pai-Yen
Rozhkova, Anastasiia
Torabi, Elahehsadat
Bagci, Hakan
Shamim, Atif
Zhang, Xianglian
KAUST Department
Electrical Engineering ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Division of Computer, Electrical, and Mathematical Science and Engineering (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
Date
2019-10-24Permanent link to this record
http://hdl.handle.net/10754/660370Metadata
Show full item recordAbstract
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.Citation
Erricolo, D., Chen, P.-Y., Rozhkova, A., Torabi, E., Bagci, H., Shamim, A., & Zhang, X. (2019). Machine Learning in Electromagnetics: A Review and Some Perspectives for Future Research. 2019 International Conference on Electromagnetics in Advanced Applications (ICEAA). doi:10.1109/iceaa.2019.8879110Conference/Event name
2019 International Conference on Electromagnetics in Advanced Applications (ICEAA)Additional Links
https://ieeexplore.ieee.org/document/8879110/https://ieeexplore.ieee.org/document/8879110/
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8879110