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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 # |
WBS, SAT (Joint) |
2017-05-25 15:50 |
Tochigi |
Utsunomiya Univ. Yoto Campus |
[Special Talk]
Dynamic Beam Control for Next Generation Mobile Communication Satellite with Large Deployable Antenna Maki Akioka, Amane Miura, Morio Toyoshima, Teruaki Orikasa, Masaki Sato, Hiroyuki Tsuji, Yoshiyuki Fujino (NICT), Tetsuji Katayama, Yoshihiro Oshida, Masahiko Sunagawa, Osamu Yoshida, Tsuyoshi Kuzumaki, Yuta Horiuchi, Yu Itoh, Keiichi Yano (Softbank) SAT2017-4 |
For mobile communication satellite for next generation satellite mobile communication service, very large aperture deplo... [more] |
SAT2017-4 pp.19-24 |
MBE, NC (Joint) |
2014-11-21 11:00 |
Miyagi |
Tohoku University |
A Comparison of Back Propagation Learning between the Inverse-function Delayless Model and a Conventional Model Yuta Horiuchi (Tohoku Univ), Yoshihiro Hayakawa (SNCT), Takeshi Onomi, Koji Nakajima (Tohoku Univ) NC2014-26 |
For the combinatorial optimization problem using the hopfield model, avoidance of the local minimum problem is important... [more] |
NC2014-26 pp.7-10 |
NLP |
2014-06-30 16:00 |
Miyagi |
Tohoku Univ. |
Backpropagation learning using inverse function delay-less model Yuta Horiuchi (Tohoku Univ.), Yoshihiro Hayakawa (SNCT), Takeshi Onomi, Koji Nakajima (Tohoku Univ.) NLP2014-25 |
The Inverse function Delayed (ID) model has been proposed as one of novel neural models. ID model has a oscillation capa... [more] |
NLP2014-25 pp.27-30 |
NLP |
2014-01-21 15:40 |
Hokkaido |
Niseko Park Hotel |
Neural Network learning using Inverse Function Delayless Model Yuta Horiuchi (Tohoku Univ.), Yoshihiro Hayakawa (SNCT), Shigeo Sato, Koji Nakajima (Tohoku Univ.) NLP2013-142 |
The Inverse function Delayed (ID) model has been proposed as one of novel neural models. The ID model has an ability of ... [more] |
NLP2013-142 pp.73-76 |
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