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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 41  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
MBE, NC, NLP, CAS
(Joint) [detail]
2020-10-29
10:50
Online Online Classification of binary data based on binary neural networks
Kento Saka, Tomoyuki Togawa, Toshimichi Saito (HU) NC2020-8
This paper presents a novel application of binary neural networks to clustering of data sets.
The network characterized... [more]
NC2020-8
pp.1-4
MBE, NC, NLP, CAS
(Joint) [detail]
2020-10-29
11:15
Online Online Dynamic binary neural networks with time-variant parameters
Takumi Suzuki, Shota Anzai, Toshimichi Saito (HU) NC2020-9
This paper studies a three-layer dynamic binary neural network with time-variant parameters and its application. The net... [more] NC2020-9
pp.5-8
NLP, CAS 2019-10-22
16:45
Gifu Gifu Univ. On transition from periodic orbits to fixed points in simple neural networks
Yuki Kawamura, Toshimichi Saito (HU) CAS2019-37 NLP2019-77
A dynamic binary neural network is a recurrent-type neural network
characterized by cross-connection parameters and sig... [more]
CAS2019-37 NLP2019-77
pp.71-75
MBE, NC 2019-10-12
10:00
Miyagi   Stability of Periodic Orbits in 3-Layer Dynamic Binary Neural Networks
Seitaro Koyama, Toshimichi Saito (HU) MBE2019-39 NC2019-30
The 3-layer dynamic binary neural networks (3-DBNNs) are characterized by ternary connection parameters and signum activ... [more] MBE2019-39 NC2019-30
p.51
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-17
13:00
Okinawa Okinawa Institute of Science and Technology Analysis and application of periodic orbits in dynamic binary neural networks
Shota Anzai, Seitaro Koyama, Toshimichi Saito (HU) NC2019-1
This paper studies a simple dynamic binary neural network and its application.
In the network, each neuron transforms ... [more]
NC2019-1
p.1
NC, MBE
(Joint)
2019-03-04
16:35
Tokyo University of Electro Communications Application of dynamic binary neural networks to central pattern generators
Shota Anzai, shunsuke aoki, seitaro koyama, Toshimichi Saito (HU) NC2018-61
This paper studies basic dynamics of simple dynamic binary neural networks and their applications.
The network is chara... [more]
NC2018-61
pp.95-98
MBE, NC
(Joint)
2018-05-19
15:20
Toyama Univ. of Toyama On Stability of Sparse Binary Neural Networks
Seitaro Koyama, Shunsuke Aoki, Toshimichi Saito (HU) NC2018-3
The dynamic binary neural network is characterized by ternary connection parameters and the signum activaion function.
... [more]
NC2018-3
pp.9-13
MBE, NC, NLP
(Joint)
2018-01-27
11:20
Fukuoka Kyushu Institute of Technology Stability and periodic orbits in dynamic binary neural newtorks
Seitaro Koyama, Shunsuke Aoki, Toshimichi Saito (HU) NLP2017-97
The dynamic binary neural network is characterized by the signum activation function and ternary connection parameters. ... [more] NLP2017-97
pp.59-62
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
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