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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| RCC, ISEC, IT, WBS | 2024-03-14 17:00 |
Osaka | Osaka Univ. (Suita Campus) | Comparison of Scale Parameter Dependence of Estimation Performance in Sparse Bayesian Linear Regression Model with Variance Gamma Prior Distribution and t-Prior Distribution Kazuaki Murayama (UEC)  IT2023-135 ISEC2023-134 WBS2023-123 RCC2023-117 |
In the sparse estimation with linear regression model, the variance gamma distribution and t-distribution can be used as... [more] | IT2023-135 ISEC2023-134 WBS2023-123 RCC2023-117 pp.374-379 |
| SIP, IT, RCS | 2024-01-18 11:45 |
Miyagi | (Primary: On-site, Secondary: Online) |
A Study on Massive MIMO Channel Estimation Based on Sparse Bayesian Learning Using Hierarchical Model Kengo Furuta, Takumi Takahashi, Kenta Ito (Osaka Univ.), Shinsuke Ibi (Doshisha Uni.) IT2023-34 SIP2023-67 RCS2023-209 |
Massive multi-input multi-output (MIMO) channels are known to have pseudo-sparsity in the angular (beam) domain, and it ... [more] | IT2023-34 SIP2023-67 RCS2023-209 pp.25-30 |
| QIT (2nd) |
2023-12-17 17:30 |
Okinawa | OIST (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Sparse identification of quantum dynamics via quantum circuit learning Yusei Tateyama, Yuzuru Kato (FUN) |
Sparse Identification of Nonlinear Dynamics (SINDy) is a data-driven method for estimation and prediction of nonlinear d... [more] | |
| EA, ASJ-H, ASJ-MA, ASJ-SP | 2023-07-03 11:35 |
Hokkaido | Consideration on Sound Source Distance Measurement by Complex Sparse Bayesian Estimation Using a Small Microphone Array System Senta Ariizumi, Teruki Toya, Kenji Ozawa (UoY) EA2023-17 |
In this study, we aim to measure the distance to a sound source by sparse Bayesian estimation using a small-scale microp... [more] | EA2023-17 pp.72-77 |
|
| AP | 2023-04-14 15:20 |
Osaka | Osaka Univ. (Primary: On-site, Secondary: Online) |
[Tutorial Lecture]
Underdetermined Direction-Of-Arrival Estimation by Sparse Arrays
-- Array Configuration Optimization for Enhancing Degree of Freedom -- Koichi Ichige (Yokohama National Univ.) AP2023-7 |
This paper introduces various sparse array configurations, and shows that underdetermined (more number of sources than t... [more] | AP2023-7 pp.34-39 |
| RCC, ISEC, IT, WBS | 2023-03-14 15:20 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
Estimation Performance of Sparse Bayesian Linear Regression model with t-distribution Kazuaki Murayama (UEC) IT2022-105 ISEC2022-84 WBS2022-102 RCC2022-102 |
In the sparse estimation with linear regression model, the t-distribution can be used as a prior distribution. We analyz... [more] | IT2022-105 ISEC2022-84 WBS2022-102 RCC2022-102 pp.236-241 |
| EST | 2023-01-26 16:00 |
Okinawa | (Primary: On-site, Secondary: Online) |
Estimation of magnetic dipole positions using sparse modeling Tomonori Yanagida, Yuji Ogata, Bunichi Kakinuma, Masayuki Kimishima (Advantest Lab) EST2022-87 |
In recent years, magnetic fields have attracted attention as applications for non-contact, non-destructive measurement o... [more] | EST2022-87 pp.70-73 |
| IT, RCS, SIP | 2023-01-24 16:20 |
Gunma | Maebashi Terrsa (Primary: On-site, Secondary: Online) |
Underdetermined DOA Estimation of Correlated Signals Using Atomic Norm Minimization Soichi Obata, Steven Wandale, Koichi Ichige (Yokohama Nat'l Univ.) IT2022-50 SIP2022-101 RCS2022-229 |
This paper discusses the underdetermined Direction-of-Arrival (DOA) estimation of correlated sources where the number of... [more] | IT2022-50 SIP2022-101 RCS2022-229 pp.120-125 |
| SIS, ITE-BCT | 2022-10-14 11:05 |
Aomori | Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
A Study of Blind Estimation for Sparse Channel Yosuke Sugiura, Kaito Shinoda, Nozomiko Yasui, Tetsuya Shimamura (Saitama Univ.) SIS2022-19 |
In this paper, we propose an estimation method for sparse channel without a pilot symbol in wireless communication based... [more] | SIS2022-19 pp.44-48 |
| RISING (3rd) |
2021-11-17 09:00 |
Tokyo | (Primary: On-site, Secondary: Online) |
Interference Estimation Method Using Sparse Modeling Based on Spectrum Database Hiroki Ito (UEC), Kei Inage (TMCIT), Takeo Fujii (UEC) |
With the Internet of Things (IoT) era, the number of devices that share the same frequency is rapidly increasing. IoT de... [more] | |
| NC, MBE (Joint) |
2021-03-04 09:50 |
Online | Online | Evaluation of effect of source noise on magnetoencephalography source estimation using a structured sparse model Kai Miyazaki, Shun Nirasawa, Kazuaki Akamatsu, Yoichi Miyawaki (UEC) NC2020-56 |
Magnetoencephalography (MEG) is a method to acquire human brain activity at a high temporal resolution, but its spatial ... [more] | NC2020-56 pp.77-82 |
| SeMI, IPSJ-MBL, IPSJ-UBI [detail] | 2021-03-02 14:30 |
Online | Online | [Poster Presentation]
Wireless channel characterization with sparse modeling Naota Takeyama, Jin Mitsugi (Keio Univ.) SeMI2020-66 |
In wireless channel characterization using adaptive filters, adaptive algorithms based on Lasso, Group Lasso, and SCAD h... [more] | SeMI2020-66 pp.47-56 |
| SIP, IT, RCS | 2021-01-21 16:50 |
Online | Online | [Invited Talk]
Recent topics on approximate message passing for sparse signal recovery Kazushi Mimura (Hiroshima City Univ.), Jun'ichi Takeuchi (Kyushu Univ.) IT2020-81 SIP2020-59 RCS2020-172 |
The approximate massage passing (AMP) that was proposed for sparse signal recovery algorithm has been widely applied to ... [more] | IT2020-81 SIP2020-59 RCS2020-172 p.100 |
| SIP | 2020-08-28 11:20 |
Online | Online | [Invited Talk]
Blind source separation based on proximal splitting algorithm Kohei Yatabe (Waseda Univ.) SIP2020-36 |
This talk presents blind source separation (BSS) from multi-channel audio signals. BSS is methodology of estimating sepa... [more] | SIP2020-36 p.31 |
| MI, IE, SIP, BioX, ITE-IST, ITE-ME [detail] | 2020-05-28 10:50 |
Online | Online | [Special Talk]
High-dimensional Signal Restoration by Convolutional Networks Driving Fusion Across Multiple Disciplines
-- Sparse Modeling and Convolutional Dictionary Learning -- Shogo Muramatsu (Niigata Univ.) |
This talk outlines a restoration process of high-dimensional signals such as image and volumetric data. With the develop... [more] | |
| ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2020-02-27 15:10 |
Hokkaido | Hokkaido Univ. (Cancelled but technical report was issued) |
A note on estimation of gaze features for human emotion estimation while viewing images Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a method for estimation of gaze features for human emotion estimation while viewing images. In the p... [more] | |
| CS, CAS | 2020-02-27 14:30 |
Kumamoto | An Estimation of Network Traffic Validation based on Sparse Coding Takayuki Nakachi, Yitu Wang (NTT) CAS2019-107 CS2019-107 |
With accurate network traffic prediction, future communication networks can realize self-management and enjoy intelligen... [more] | CAS2019-107 CS2019-107 pp.55-60 |
|
| SAT, SANE (Joint) |
2020-02-20 10:25 |
Okinawa | Experimental Study on 2-D Human Position Estimation by Passive Radar Using Wireless LAN Tatsuya Ogawa, Masanori Gocho, Hiroyoshi Yamada (Niigata Univ.) SANE2019-119 |
In recently years radio system have been studied intensively. Especially, the indoor human location estimation for secur... [more] | SANE2019-119 pp.113-118 |
|
| RCC, ITS, WBS | 2019-11-06 11:00 |
Nara | Nara Institute of Science and Technology | [Poster Presentation]
Precision comparison of channel estimation in single-carrier FDMA using compressed sensing technique Haohui Jia, Takeshi Higashino, Minoru Okada (NAIST) WBS2019-29 ITS2019-20 RCC2019-60 |
Single carrier frequency division multiple access (SC-FDMA) system re- duces a peak to average power ratio comparing wit... [more] | WBS2019-29 ITS2019-20 RCC2019-60 pp.31-36 |
| SANE | 2019-10-31 11:20 |
Overseas | KOREA (Jeju) | Experimental Study on Human Position Estimation by Passive Radar Using Wireless LAN Tatsuya Ogawa, Masanori Gocho, Hiroyoshi Yamada (Niigata Univ.) SANE2019-51 |
In recent years, research on indoor position estimation using radio wave sensors has been actively conducted. However, t... [more] | SANE2019-51 pp.25-28 |
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