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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 # |
EST |
2023-01-26 14:50 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Design of thin dielectric lens for millimeter-wave antenna using high dielectric constant materials Keiichi Itoh, Junya Satoh, Shun Togase, Masaki Tanaka (NIT, Akita College), Hajime Igarashi (Hokkaido Univ.) EST2022-84 |
This paper describes a design method for thin dielectric lenses for millimeter-wave antennas using high dielectric const... [more] |
EST2022-84 pp.53-57 |
EST |
2021-01-21 16:25 |
Online |
Online |
Shape design of THz liquid crystal devices and application to metamaterials Yuta Sato, Masaki Tanaka (NIT, Akita), Tomoyuki Sasaki (NUT), Keiichi Itoh (NIT, Akita) EST2020-64 |
Today, it is an urgent issue to develop active devices that control the terahertz wave propagation in order to further e... [more] |
EST2020-64 pp.62-67 |
MW, EMCJ, EST, IEE-EMC [detail] |
2017-10-20 13:10 |
Akita |
Yupopo |
Topology optimization of dielectric lens antenna using normalized Gaussian network Keiichi Itoh (NIT, Akita College), Hajime Igarashi (Hokkaido Univ.) EMCJ2017-48 MW2017-100 EST2017-63 |
This paper reports a novel 3D topology optimization method based on the finite difference time domain (FDTD) method for ... [more] |
EMCJ2017-48 MW2017-100 EST2017-63 pp.123-127 |
NC, MBE (Joint) |
2009-03-12 13:50 |
Tokyo |
Tamagawa Univ. |
Model Learning of Normalized Gaussian Networks Using On-line Information Bottleneck EM Algorithm Satoshi Imai, Hiroyuki Seki (Nara Inst. of Sci and Tech.) NC2008-143 |
In this report, we propose a new learning method of stochastic models which have hidden variables.
This method estimate... [more] |
NC2008-143 pp.237-242 |
NC |
2006-03-16 14:30 |
Tokyo |
Tamagawa University |
Application of a Forward-propagation Learning Rule for Adaptive Motor Control with Mixture Models Yoshihiro Ohama, Naohiro Fukumura, Yoji Uno (Toyohashi Univ. Tech.) |
We have proposed a forward-propagation learning (FPL) rule for acquiring neural inverse models. FPL can solve a credit a... [more] |
NC2005-145 pp.121-126 |
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