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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-14 13:25 |
Online |
Online |
Angular-Frequency Wideband Spectrum Sensing based on Multi-Coset Sampling Azril Haniz, Takeshi Matsumura, Fumihide Kojima (NICT) SR2021-21 |
For future 5G and Beyond 5G (B5G) networks employed in mmWave spectrum that use beamforming with massive MIMO arrays, it... [more] |
SR2021-21 pp.9-15 |
SANE, SAT (Joint) |
2019-02-14 10:00 |
Kagoshima |
Tanegashima Island |
Sparse Frequency-Step Design using Compressive Sensing in Stepped Multiple Frequency Pulse Radar Takayuki Inaba, Manabu Akita (UEC) SANE2018-113 |
In this article, a sparse frequency-step design method using Compressive Sensing (CS) in multiple stepped pulse radar fo... [more] |
SANE2018-113 pp.19-24 |
EMT, IEE-EMT |
2017-06-02 13:00 |
Tokyo |
Nihon University |
Realtime 3D image reconstruction methods based on compressive sensing with CUDA support Iakov Chernyak, Motoyuki Sato (Tohoku Univ.) EMT2017-3 |
We developed a number of GPU optimized 3D radar image reconstruction algorithms and applied it for the 3D sparse array r... [more] |
EMT2017-3 pp.19-24 |
RCS, AP (Joint) |
2016-11-24 14:20 |
Kyoto |
Kyoto International Community House |
[Invited Lecture]
Evaluation of Propagating-Path Identification Combining FDTD Method and Compressive Sensing Tomohiro Komatsu, Naoki Honma, Yoshitaka Tsunekawa (Iwate Univ.) AP2016-112 RCS2016-196 |
In this paper, we evaluate the propagating-path identification using FDTD (Finite-Difference Time-Domain) method and com... [more] |
AP2016-112 RCS2016-196 pp.29-34 |
MI |
2015-03-02 09:17 |
Okinawa |
Hotel Miyahira |
4D-MRI Reconstruction using the low-rank plus sparse matrix decomposition Yukinojo Kitakami, Takashi Ohnishi, Yoshitada Masuda (Chiba Univ. Engineering), Koji Matsumoto (Chiba University Hospital), Hideaki Haneishi (Chiba Univ. Engineering) MI2014-54 |
4D-MRI can visualize and quantify the three-dimensional dynamics of the thoracoabdominal respiratory movement and allows... [more] |
MI2014-54 pp.7-11 |
SR, AN, USN, RCS (Joint) |
2012-10-18 16:50 |
Fukuoka |
Fukuoka univ. |
[Invited Talk]
Applications of Compressed Sensing in Wireless Communication Systems Doohwan Lee (Univ. of Tokyo) RCS2012-145 SR2012-65 AN2012-39 USN2012-42 |
Compressed sensing has been drawn explosive attention during last several years. It is a new framework that uses signal ... [more] |
RCS2012-145 SR2012-65 AN2012-39 USN2012-42 p.121(RCS), p.179(SR), p.91(AN), p.85(USN) |
RCS, AN, MoNA, SR (Joint) |
2010-03-05 15:30 |
Kanagawa |
YRP |
A Heterogeneous Network System with Flexible Access Points and Protocol-free Signal Processing Part
-- Part2: Highly Efficient Radio Wave Data Compression Method Employing Compressed Sensing Technology -- Doohwan Lee, Takayuki Yamada, Hiroyuki Shiba, Yo Yamaguchi, Kazuhiro Uehara (NTT Corp.) RCS2009-322 MoMuC2009-95 SR2009-119 AN2009-88 |
Rapid developments and changes of wireless radio environments require a unified platform which can flexibly deal with va... [more] |
RCS2009-322 MoMuC2009-95 SR2009-119 AN2009-88 pp.379-384(RCS), pp.129-134(MoMuC), pp.189-194(SR), pp.117-122(AN) |
SR |
2010-01-21 11:30 |
Tokyo |
Univ. of Electro-Communications |
Combined Nyquist and compressed sampling method for the wireless multiband receiver Doohwan Lee, Takayuki Yamada, Hiroyuki Shiba, Yo Yamaguchi, Kazuhiro Uehara (NTT) SR2009-77 |
The recently developed compressed sensing theory enables signal recovery from incomplete information with high probabili... [more] |
SR2009-77 pp.21-26 |
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