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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 16:20 |
Okinawa | (Primary: On-site, Secondary: Online) |
Residual Noise Reduction Based on Sound Source Signal Independence Kai Furusawa, Kenji Suyama (Tokyo Denki Univ.)  EA2023-90 SIP2023-137 SP2023-72 |
We have developed a method based on the multiplication of multiple weighted sum circuits output as a directionality form... [more] | EA2023-90 SIP2023-137 SP2023-72 pp.174-179 |
| R | 2023-12-07 14:40 |
Tokyo | Kikai-Shinko-Kaikan Bldg (Primary: On-site, Secondary: Online) |
Optimal CBM policy for a degrading system with two weighted components Shinji Kawano, Nobuyuki Tamura (Hosei Univ.) R2023-51 |
We consider a system in which the degradation of two components follows a Wiener process with different drifts, and a fa... [more] | R2023-51 pp.6-11 |
| IT, RCS, SIP | 2023-01-24 10:00 |
Gunma | Maebashi Terrsa (Primary: On-site, Secondary: Online) |
A hierarchical construction of typical linear codes Kaito Suzuki, Tomohiko Uyematsu (Tokyo Tech.) IT2022-35 SIP2022-86 RCS2022-214 |
According to Shannon's channel coding theorem, a channel has an inherent amount called a channel capacity which is deter... [more] | IT2022-35 SIP2022-86 RCS2022-214 pp.36-41 |
| SIS, ITE-BCT | 2022-10-14 10:00 |
Aomori | Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
Robust Semi-Supervised Learning for Noisy Labels Using Early-learning Regularization and Weighted Loss Ryota Higashimoto, Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) SIS2022-16 |
Training Deep Neural Networks (DNNs) on datasets with incorrect labels (label noise) is an important challenge. In the p... [more] | SIS2022-16 pp.27-32 |
| IA, CQ, MIKA (Joint) |
2022-09-15 16:25 |
Hokkaido | Hokkaido Citizens Actives Center (Primary: On-site, Secondary: Online) |
Impact of Hashrate on Theoretical Fork Rate of Blockchain Sakurai Akira (Tokyo Tech), Shudo Kazuyuki (Kyoto Univ.) IA2022-20 |
Blockchain divergence, or forks, make it less secure. So the fork rate can be used as a measure of security. Theoretica... [more] |
IA2022-20 pp.32-35 |
| IT | 2021-07-08 13:00 |
Online | Online | Equivalence classes of the cosets of a subcode for the extended binary primitive BCH codes of length 512 and 1024 Mine Arai, Toru Fujiwara (Osaka Univ.) IT2021-15 |
Suppose that cosets by subcodes for extended binary primitive BCH codes. If the subcodes are extended binary primitive B... [more] | IT2021-15 pp.1-5 |
| EMM, IT | 2019-05-23 15:55 |
Hokkaido | Asahikawa International Conference Hall | The Weight Distributions of the (256,k) Extended Binary Primitive BCH Codes with k=71, 187, 191, and 199 Toru Fujiwara (Osaka Univ.), Takuya Kusaka (Okayama Univ.) IT2019-5 EMM2019-5 |
Computing the weight distribution of a code when the formula for the distribution is unknown is a challenging problem in... [more] | IT2019-5 EMM2019-5 pp.23-28 |
| IT, ISEC, WBS | 2019-03-08 16:10 |
Tokyo | University of Electro-Communications | Studies on Ordered Shuffled BP Decoding of LDPC Codes
-- Based on the Loops and Weight Distributions of LDPC Codes -- Ryoma Sakai, Arisa Matsuo, Kazuhiko Yamaguchi (UEC) IT2018-128 ISEC2018-134 WBS2018-129 |
In the Shuffled BP decoding of LDPC codes, the decoding order has a large influence on BER performance. Previous resear... [more] | IT2018-128 ISEC2018-134 WBS2018-129 pp.319-324 |
| IT | 2017-09-08 09:50 |
Yamaguchi | Centcore Yamaguchi Hotel | On the weight distributions of the binary codes obtained from Reed-Solomon codes over GF(2^m) Tshihisa Nishijima (Hosei Univ.) IT2017-40 |
In this report, we give a necessary and sufficient condition for symmetry of the weight distribution of the binary ... [more] | IT2017-40 pp.11-14 |
| IT | 2017-07-14 13:45 |
Chiba | Chiba University | Unequal Error Protection Codes Based on Reed-Solomon Codes over $GF(2^{m})$ Toshihisa Nishijima (Hosei Univ.) IT2017-32 |
A new class of unequal error protection codes based on Reed-Solomon codes over $GF(2^{m})$ is proposed by using the codi... [more] | IT2017-32 pp.91-95 |
| SR | 2017-05-25 11:05 |
Tokyo | Tokyo big sight | Spectrum Management with Weighted Combining of Sensing Results for Wireless LAN over White Space Spectrum Shigenobu Sasaki, Ryota Hoshino (Niigata Univ.) SR2017-3 |
In this paper, a spectrum management algorithm based on weighted combining of spectrum sensing results is proposed for w... [more] | SR2017-3 pp.13-18 |
| EA, US (Joint) |
2017-01-25 13:00 |
Kyoto | Doshisha Univ. | [Poster Presentation]
Directive beamforming based on probability weighted least square Ryusuke Tanaka, Yoichi Haneda (UEC) EA2016-70 |
Directivity beamforming using a microphone array has been currently implemented for noise suppres- sion in video confer... [more] |
EA2016-70 pp.13-18 |
| IT, SIP, RCS | 2017-01-19 10:25 |
Osaka | Osaka City Univ. | On the Error Performance of Network Coded Cooperation over Flat Fading Channel Hironori Soen, Motohiko Isaka (Kwansei Gakuin Univ.) IT2016-52 SIP2016-90 RCS2016-242 |
We discuss the performance of wireless network coded cooperation where multiple communication nodes send each one’s mess... [more] | IT2016-52 SIP2016-90 RCS2016-242 pp.35-40 |
| VLD, DC, CPSY, RECONF, CPM, ICD, IE (Joint) [detail] |
2016-11-30 09:00 |
Osaka | Ritsumeikan University, Osaka Ibaraki Campus | Fast Test Pattern Reordering Based on Weighted Fault Coverage Shingo Inuyama, Kazuhiko Iwasaki (Tokyo Metropolitan Univ.), Masayuki Arai (Nihon Univ.) VLD2016-61 DC2016-55 |
Shrinking feature size and higher integration on semiconductor device manufacturing technology bring a problem of the ga... [more] | VLD2016-61 DC2016-55 pp.99-104 |
| PRMU, IE, MI, SIP | 2016-05-19 16:50 |
Aichi | [Special Talk]
Two approaches to image motion detection: temporal vs. spatial weighted integral method Shigeru Ando (University of Tokyo) SIP2016-14 IE2016-14 PRMU2016-14 MI2016-14 |
Optical flow detection is an identification problem of spatio-temporal partial differential equation (PDE).The weighted ... [more] | SIP2016-14 IE2016-14 PRMU2016-14 MI2016-14 pp.71-78 |
|
| MI | 2016-01-19 10:48 |
Okinawa | Bunka Tenbusu Kan | Spatiotemporal Statistical Shape Model Construction Using Weighted PCA Ryosuke Nakano, Saadia Binte Alam, Syoji Kobashi, Masakazu Morimoto, Satoru Aikawa (Univ of Hyogo), Akinobu Shimizu (Tokyo Univ of Agriculture and Technology) MI2015-77 |
Statistical shape model (SSM), which represents a static organ shape, has been applied to some medical image understandi... [more] | MI2015-77 pp.25-29 |
| AP | 2015-02-19 10:20 |
Hyogo | Chusho-kigyou center at Amagasaki-City | Probability Distribution of Combined Signal Intensity for Imperfect MRC Yoshio Karasawa (UEC) AP2014-188 |
Diversity order of MRC in i.i.d. Rayleigh fading environment for N-antenna system is known as N. In that case, obtaining... [more] | AP2014-188 pp.11-14 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Target Shift Adaptation for Conditional Density Estimation and Regression Tuan Duong Nguyen (Tokyo Inst. of Tech.), Marthinus Christoffel du Plessis, Masashi Sugiyama (Univ. of Tokyo) IBISML2014-55 |
We consider the problem of domain adaptation under target shift scenario, where the target marginal distributions p(y) d... [more] | IBISML2014-55 pp.155-160 |
| SR | 2013-10-25 15:30 |
Osaka | Osaka Univ. | Weighted Cooperative Sensing Based on Database for Cognitive Vehicular Networks Yuya Ohue, Masayuki Kitamura, Kei Inage, Takeo Fujii (Univ. of Electro-Comm.) SR2013-73 |
A cognitive radio has been attracted attention as the promising technique to improve the spectral efficiency. In the rec... [more] | SR2013-73 pp.117-122 |
| NC | 2012-10-05 10:00 |
Fukuoka | Kyushu Institute of Technology (Wakamatsu Campus) | The modulation of long-term depression affecting distance-dependent synaptic weight distribution and directional spike propagation in a recurrent network Toshikazu Samura, Eriko Sugisaki, Yutaka Sakai (Tamagawa Univ.), Hatsuo Hayashi (KYUTECH), Takeshi Aihara (Tamagawa Univ.) NC2012-49 |
A recurrent network where excitatory and inhibitory neurons are mutually connected causes spike propagation when excitat... [more] | NC2012-49 pp.73-78 |
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