Beamspace-domain learning of minimum variance beamformer with fully convolutional network

Hiki Ryuichi, Mozumi Michiya, Omura Masaaki, Nagaoka Ryo, Hasegawa Hideyuki

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

Original language	Japanese
Pages (from-to)	SJ1050-SJ1050
Journal	Japanese Journal of Applied Physics
Volume	62
Issue number	SJ
DOIs	https://doi.org/10.35848/1347-4065/acbda2
State	Published - 2023
Externally published	Yes

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@article{4e6403c233e2480393e43fb47155e263,

title = "Beamspace-domain learning of minimum variance beamformer with fully convolutional network",

author = "Hiki Ryuichi and Mozumi Michiya and Omura Masaaki and Nagaoka Ryo and Hasegawa Hideyuki",

year = "2023",

doi = "10.35848/1347-4065/acbda2",

language = "日本",

volume = "62",

pages = "SJ1050--SJ1050",

journal = "Japanese Journal of Applied Physics",

number = "SJ",

}

TY - JOUR

T1 - Beamspace-domain learning of minimum variance beamformer with fully convolutional network

AU - Ryuichi, Hiki

AU - Michiya, Mozumi

AU - Masaaki, Omura

AU - Ryo, Nagaoka

AU - Hideyuki, Hasegawa

PY - 2023

Y1 - 2023

U2 - 10.35848/1347-4065/acbda2

DO - 10.35848/1347-4065/acbda2

M3 - 学術論文

VL - 62

SP - SJ1050-SJ1050

JO - Japanese Journal of Applied Physics

JF - Japanese Journal of Applied Physics

IS - SJ

ER -