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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 21 - 40 of 53 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SDM, ICD, ITE-IST [detail] 2017-08-02
10:15
Hokkaido Hokkaido-Univ. Multimedia Education Bldg. SDM2017-43 ICD2017-31 (To be available after the conference date) [more] SDM2017-43 ICD2017-31
pp.101-106
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] 2017-06-24
09:30
Okinawa Okinawa Institute of Science and Technology Elementary cellular automata and dynamic binary neural networks
Takahiro Ozawa, Kazuma Makita, Toshimichi Saito (Hosei Univ.) NC2017-13
This paper studies basic dynamic of elementary cellular automata(ECA):
digital dynamical systems in which time, space a... [more]
NC2017-13
pp.93-97
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] 2017-06-24
09:55
Okinawa Okinawa Institute of Science and Technology Stability of fixed points and periodic orbits in dynamic binary neural networks
Seitaro Koyama, Shunsuke Aoki, Toshimichi Saito (Hosei Univ.) NC2017-14
The dynamic neural networks are characterized by the signum activation function and ternary connection parameters.
Depe... [more]
NC2017-14
pp.99-103
MBE, NC
(Joint)
2017-03-13
11:15
Tokyo Kikai-Shinko-Kaikan Bldg. Stability and Sparsity of Dynamic Binary Neural Networks
Shunsuke Aoki, Ryuji Sato, Toshimichi Saito (HU) NC2016-81
This paper studies relation between sparsification and stability of a desired binary periodic orbit in the dynamic binar... [more] NC2016-81
pp.103-107
NC, NLP
(Joint)
2017-01-27
13:00
Fukuoka Kitakyushu Foundation for the Advanement of Ind. Sci. and Tech. Dynamic Binary Neural Networks with Local Connection
Kazuma Makita, Toshimichi Saito (HU) NC2016-57
This paper studies of dynamic binary neural networks.
The network is characterized by a signum activation fuction and ... [more]
NC2016-57
pp.53-57
MBE, NC
(Joint)
2016-12-07
13:30
Aichi Toyohashi University of Technology NC2016-40 This paper studies relation between sparsification and stability of desired binary periodic orbits in the dynamic binary... [more] NC2016-40
pp.1-5
CAS, NLP 2016-10-27
09:30
Tokyo   On sparsification of Dynamic Binary Neural Networks
Shunsuke Aoki, Ryuji Sato, Toshimichi Saito (HU) CAS2016-38 NLP2016-64
This paper studies sparsification effects of connection parameters in dynamic binary neural networks. The network is cha... [more] CAS2016-38 NLP2016-64
pp.1-4
MBE, NC
(Joint)
2016-05-21
13:00
Toyama University of Toyama Simple feature quantities of periodic orbits in dynamic binary neural networks
Kazuma Makita, Ryuji sato, Toshimichi Saito (HU) NC2016-1
This paper studies perodic orbits of dynamic binary neural networks.
The network is characterized by a signum activati... [more]
NC2016-1
pp.1-4
NC, NLP
(Joint)
2016-01-29
13:35
Fukuoka Kyushu Institute of Technology Analysis of periodic orbits in dynamic binary neural networks
Kazuma Makita, Ryuji Sato, Toshimichi Saito (HU) NC2015-61
This paper considers analysis of dynamic binary neural networks.
The networks can generate various binary periodic orb... [more]
NC2015-61
pp.25-28
NLP, CAS 2015-10-05
11:10
Hiroshima Aster Plaza Learning of Dynamic Binary Neural Networks by Sparsification
Ryuji Sato, Toshimichi Saito (HU) CAS2015-23 NLP2015-84
This paper studies learning of the dynamic binary neural network that can generate various binary periodic orbits. The l... [more] CAS2015-23 NLP2015-84
pp.15-20
NC, IPSJ-BIO, IBISML, IPSJ-MPS
(Joint) [detail]
2015-06-25
15:45
Okinawa Okinawa Institute of Science and Technology Learning of dynamic binary neural networks based on the simple feature quantity
Ryuji Sato, Toshimichi Saito (HU) NC2015-9
This paper studies learning of the dynamic binary neural network that can generate various binary periodic orbits. The l... [more] NC2015-9
pp.83-87
MBE, NC
(Joint)
2014-12-13
13:20
Aichi Nagoya University Consideration of Dynamic Binary Neural Networks based on the Feature Quantity Plane
Ryuji Sato, Jungo Moriyasu, Toshimichi Saito (Hosei Univ.) NC2014-51
This paper studies learning the 2-layer dynamic binary neural network that can generate various binary periodic orbit.
... [more]
NC2014-51
pp.43-47
NC, MBE
(Joint)
2014-03-18
15:20
Tokyo Tamagawa University A learning method for dynamic binary neural networks using a particle swarm optimizer
Romu Nagano, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NC2013-113
This paper proposes a new learning algorithm to the dynamic binary neural network (DBNN). The proposed method aims to im... [more] NC2013-113
pp.145-149
SP, IPSJ-SLP
(Joint)
2013-07-25
15:10
Miyagi Soho (togatta spa) Effectiveness of discriminative approaches for speech recognition under noisy environments on the 2nd CHiME Challenge
Yuuki Tachioka (Mitsubishi Electric), Shinji Watanabe, Jonathan Le Roux, John R Hershey (MERL) SP2013-55
The 2nd CHiME challenge is a difficult two-microphone speech recognition task with non-stationary interference. We inves... [more] SP2013-55
pp.13-18
NC, MBE
(Joint)
2012-12-12
09:50
Aichi Toyohashi University of Technology An Application of Dynamic Binary Networks: Learning of Switching Signals of Matrix Converters
Yuta Nakayama, Toshimichi Saito (HU) NC2012-76
This paper studies a dynamic binary neural networks (DBNN) and its learning of periodic binary sequence.
As an applica... [more]
NC2012-76
pp.13-18
MBE, NC
(Joint)
2012-03-14
17:40
Tokyo Tamagawa University Analysis of Learning Process of Dynamics Binary Neural Networks
Yuta Nakayama, Ryo Ito, Toshimichi Saito (HU) NC2011-148
This paper studies a dynamic binary neural networks (DBNN) for learning of $N$-bit binary sequence.
We consider that t... [more]
NC2011-148
pp.159-164
CAS, NLP 2011-10-21
17:20
Shizuoka Shizuoka Univ. Logical Synthesis based on ART-Maps
Yusuke Okamoto, Yuta Nakayama, Yoko Enosawa, Toshimichi Saito (HU) CAS2011-62 NLP2011-89
This paper presents an application of the adaptive resonance theory map to learning algorithm of binary neural networks ... [more] CAS2011-62 NLP2011-89
pp.169-173
NLP 2011-05-27
09:35
Kagawa Olive park olive memorial hall Learning of binary neural networks for logical synthesis
Yuta Nakayama, Ryo Ito, Toshimichi Saito (HU) NLP2011-11
This paper studies a learning algorithm of binary neural networks (BNN) and its application to logical synthesis. The ne... [more] NLP2011-11
pp.49-53
NC, MBE
(Joint)
2011-03-07
17:40
Tokyo Tamagawa University Learning of Binary Neural Networks based on genetic algorithm
Ryo Ito, Toshimichi Saito (HU) NC2010-157
This paper presents a dynamic binary neural network for learing of $N$-bit binary sequence. Basically, the network is co... [more] NC2010-157
pp.177-182
NLP 2010-11-20
09:55
Miyagi Tohoku University (RIEC) An Approach to Logical Synthesis by Binary Neural Networks
Yuta Nakayama, Ryo Ito, Toshimichi Saito (Hosei Univ.) NLP2010-108
This paper studies a genetic-algorithm-based learning of binary neural networks (BNN) and its realization function of Bo... [more] NLP2010-108
pp.43-47
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