Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
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 |
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 |
BioX, SIP, IE, ITE-IST, ITE-ME [detail] |
2023-05-19 10:30 |
Mie |
Sansui Hall, Mie University (Primary: On-site, Secondary: Online) |
Privacy Preserving Deep Unrolling Methods using Random Unitary Transform Nichika Yuge, Takayuki Nakachi, Morikazu Nakamura (Univ. of the Ryukyus.) SIP2023-10 BioX2023-10 IE2023-10 |
Edge and cloud computing has been spreading in many fields including machine learning.Sparse modeling attracts attention... [more] |
SIP2023-10 BioX2023-10 IE2023-10 pp.41-46 |
EMM |
2023-01-26 13:35 |
Miyagi |
Tohoku Univ. (Primary: On-site, Secondary: Online) |
Audio zero-watermarking method based on auditory spectral representation Atsuki Ichikawa, Masashi Unoki (JAIST) EMM2022-65 |
Audio zero-watermark technique creates a detection key from watermark and binary pattern generated from features of the ... [more] |
EMM2022-65 pp.20-25 |
SANE |
2022-08-18 16:20 |
Hokkaido |
(Primary: On-site, Secondary: Online) |
Parallelization of compressive sensing SAR imaging on server and embedded GPU systems Masato Gocho (Mitsubishi Electric), Kazunori Ueda (Waseda Univ.) SANE2022-40 |
CS-SAR (compressive sensing synthetic aperture radar) imaging, in which truncated signals are observed and reconstructed... [more] |
SANE2022-40 pp.38-43 |
IA, ICSS |
2021-06-22 11:15 |
Online |
Online |
A Solution for Recovering Missing Links in Network Topology using Sparse Modeling Ryotaro Matsuo, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2021-14 ICSS2021-14 |
In recent years, sparse modeling, which is a statistical approach, has been applied to many practical problems mostly in... [more] |
IA2021-14 ICSS2021-14 pp.74-79 |
IA |
2020-10-01 13:15 |
Online |
Online |
A Study on Recovering Network Topology with Missing Links using Sparse Modeling Ryotaro Matsuo, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2020-3 |
In recent years, sparse modeling, which is a statistical approach, has been applied to many practical problems mostly in... [more] |
IA2020-3 pp.10-13 |
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 |
IE, CS, IPSJ-AVM, ITE-BCT [detail] |
2019-12-05 11:40 |
Iwate |
Aiina Center |
[Special Talk]
Representation of moving-image's sparsity and its applications to adaptive moving-image restoration Takahiro Saito (Kanagawa Univ.) CS2019-75 IE2019-55 |
This talk states that statistical sparsity of a moving-image sequence can be properly represented in the domain of the 3... [more] |
CS2019-75 IE2019-55 pp.29-34 |
MIKA (2nd) |
2019-10-03 13:35 |
Hokkaido |
Hokkaido Univ. |
[Invited Lecture]
DOA Estimation Using Sparse Modeling Toshihiko Nishimura, Seigi Nakatsu, Takeo Ohgane, Yasutaka Ogawa (Hokkaido Univ.) |
The problem of estimating the direction of arrival (DOA) of radio waves from signals received by multiple antennas is a ... [more] |
|
IE, EMM, LOIS, IEE-CMN, ITE-ME, IPSJ-AVM [detail] |
2019-09-19 15:10 |
Niigata |
Tokimeito, Niigata University |
Secure sparse representations in L0 norm minimization Takayuki Nakachi (NTT), Hitoshi Kiya (Tokyo Metro. Univ.) LOIS2019-11 IE2019-24 EMM2019-68 |
In this paper, we propose a method to estimate secure sparse representations in L0 norm minimization, and evaluate the e... [more] |
LOIS2019-11 IE2019-24 EMM2019-68 pp.25-30 |
SIS |
2019-03-06 15:10 |
Tokyo |
Tokyo Univ. Science, Katsushika Campus |
Secure Computation of Sparse Dictionary Learning Takayuki Nakachi, Yukihiro Bandoh (NTT), Hitoshi Kiya (Tokyo Metro. Univ.) SIS2018-43 |
With the advent of the big data era, all digital contents continue to increase. Sparse modeling is drawing attention as ... [more] |
SIS2018-43 pp.35-40 |
NC, MBE (Joint) |
2019-03-05 15:25 |
Tokyo |
University of Electro Communications |
Periodic Interference Cancellation Including Steep Characteristic Change With Adaptive Filter Kengo Kamei, Naohiro Toda (Aichi Pref. Univ.), Katsuyuki Hagiwara (Mie Univ.) MBE2018-100 |
When measuring bioelectric signals such as electroretinogram(ERG), periodic interference originated from power lines bec... [more] |
MBE2018-100 pp.71-76 |
SANE |
2018-10-12 11:45 |
Tokyo |
The University of Electro-Communications |
Evaluation of Range Estimation Accuracy by Wideband Coherent Processing for Sparse Frequency Bands Kazuhiro Watanabe, Manabu Akita, Takayuki Inaba (EUC) SANE2018-49 |
Ultra-wideband is becoming available in short range radar, and further higher resolution is expected by utilizing ultra-... [more] |
SANE2018-49 pp.29-34 |
IEE-CMN, EMM, LOIS, IE, ITE-ME [detail] |
2018-09-27 13:50 |
Oita |
Beppu Int'l Convention Ctr. aka B-CON Plaza |
Image Patch Modeling in Encrypted Domain using Sparse Coding Takayuki Nakachi (NTT), Hitoshi Kiya (Tokyo Metro. Univ.) LOIS2018-12 IE2018-32 EMM2018-51 |
Sparse coding represents observed signals effectively as a linear combination of a small number of bases which are chose... [more] |
LOIS2018-12 IE2018-32 EMM2018-51 pp.13-18 |
ICSS, IA |
2018-06-26 09:50 |
Ehime |
Ehime University |
Proposal of Sparse-Modeling based Approach for Betweenness Centrality Estimation Ryotaro Matsuo, Ryo Nakamura, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2018-10 ICSS2018-10 |
In recent years, a statistical approach for estimating unobserved model parameters from a small number of observations u... [more] |
IA2018-10 ICSS2018-10 pp.61-66 |
PRMU, MI, IE, SIP |
2018-05-17 17:00 |
Gifu |
|
[Invited Talk]
Statistical Modeling of 3-D DFT Coefficients of Moving Images and Its Applications to Video Restoration Takahiro Saito, Takashi Komatsu (Kanagawa Univ.) SIP2018-6 IE2018-6 PRMU2018-6 MI2018-6 |
Recently we have presented moving-image denoising with 3-D Mean-Separation-type Short-Time DFT and demonstrated that it ... [more] |
SIP2018-6 IE2018-6 PRMU2018-6 MI2018-6 pp.23-28 |
AP, WPT (Joint) |
2018-01-19 11:30 |
Nara |
ATR |
Performance Improvement by Two-step Search Method in DOA Estimation Based on Sparse Reconstruction Toshiya Nasu, Nobuyoshi Kikuma, Kunio Sakakibara (NITech) AP2017-167 |
In recent years, researches for applying signal-processing techniques based on sparse reconstruction and compressed sens... [more] |
AP2017-167 pp.93-98 |
IA |
2017-11-15 16:05 |
Overseas |
KMITL, Bangkok, Thailand |
A Solution of Minimum Link Flow Problem with Sparse Modeling
-- Formulation and Preliminary Results -- Ryotaro Matsuo, Ryo Nakamura, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2017-34 |
In recent years, a statistical approach for estimating unobserved model parameters from a small number of observations u... [more] |
IA2017-34 pp.23-26 |
IA, ICSS |
2017-06-09 09:55 |
Kochi |
Kochi University of Technolo, Eikokuji Campus |
A Solution for Minimum Link Flow Problem with Sparse Modeling Ryotaro Matsuo, Ryo Nakamura, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2017-10 ICSS2017-10 |
In recent years, a statistical approach for estimating unobserved model parameters from a small number of measurements u... [more] |
IA2017-10 ICSS2017-10 pp.53-58 |