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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 5 of 5  /   
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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