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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 30  /  [Next]  
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
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