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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLP, MSS | 2023-03-15 15:15 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Hippocampal CA3 spiking neural network model for constructing never-experienced novel path sequences on a maze task Kensuke Takada, Katsumi Tateno (Kyushu Inst. Tech.)  MSS2022-74 NLP2022-119 |
Hippocampal neurons that represent the animal's self-location are called "place cells." In the maze task in rodents, hip... [more] | MSS2022-74 NLP2022-119 p.64 |
| NC, NLP | 2023-01-29 10:15 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Low complexity of neural activity caused by weak inhibition in spiking neural networks Jihoon Park (NICT/Osaka Univ.), Yuji Kawai (Osaka Univ.), Minoru Asada (IPUT Univ./Osaka Univ./Chubu Univ./NICT) NLP2022-96 NC2022-80 |
The balance between excitatory and inhibitory neuronal activities (E/I) is an essential factor to perform normal functio... [more] | NLP2022-96 NC2022-80 pp.81-86 |
| MBE, NC (Joint) |
2022-03-03 11:10 |
Online | Online | Basic characteristics of SAM spiking neuron model with rate coding Minoru Motoki (Kumamoto KOSEN) NC2021-63 |
he SAM neuron model is one of spiking neural networks that have high computational efficiency and familiarity for digita... [more] | NC2021-63 pp.88-93 |
| CCS | 2020-11-26 15:25 |
Online | Online | Synthesis and implementation of digital spiking neurons Tomoki Harada, Toshimichi Saito (HU) CCS2020-18 |
This paper studies implementation of desired digital spike-trains based on simple evolutionary algorithm. First, the dy... [more] |
CCS2020-18 pp.6-10 |
| MBE, NC, NLP, CAS (Joint) [detail] |
2020-10-29 15:20 |
Online | Online | Unsupervised learning based on local interactions between reservoir and readout neurons Tstuki Kato, Satoshi Moriya, Hideaki Yamamoto, Masao Sakuraba, Shigeo Sato (Tohoku Univ.) NC2020-12 |
Reservoir computing is suitable for implementations in edge computing devices thanks to its low computational cost and e... [more] | NC2020-12 pp.21-23 |
| IPSJ-SLDM, RECONF, VLD, CPSY, IPSJ-ARC [detail] | 2020-01-23 14:45 |
Kanagawa | Raiosha, Hiyoshi Campus, Keio University | Study of a Simplified Digital Spiking Neuron and Its FPGA Implementation Tomohiro Yoneda (NII) VLD2019-75 CPSY2019-73 RECONF2019-65 |
A simplified digital spiking neural network implementable on FPGAs is proposed in order to reduce necessary resources an... [more] | VLD2019-75 CPSY2019-73 RECONF2019-65 pp.135-140 |
| NC, MBE | 2019-12-06 10:10 |
Aichi | Toyohashi Tech | Implementation of Cerebellar Spiking Neural Network Model on a FPGA Yusuke Shinji (Chubu Univ.), Hirotsugu Okuno (OIT), Yutaka Hirata (Chubu Univ.) MBE2019-46 NC2019-37 |
The cerebellum is crucially involved in motor control and learning. Its neuronal network architecture and firing propert... [more] | MBE2019-46 NC2019-37 pp.7-12 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-17 14:15 |
Okinawa | Okinawa Institute of Science and Technology | Effects of excitatory/inhibitory balance of a spiking neuron model on the organization of neural network Jihoon Park, Motohiro Ogura, Yuji Kawai, Minoru Asada (Osaka Univ.) NC2019-4 |
In this study, a spiking neural network model is examined to study how the balance between excitatory and inhibitory neu... [more] | NC2019-4 pp.15-20 |
| CCS | 2019-03-26 13:30 |
Tokyo | NICT, Koganei, Tokyo | Various synchronization phenomena in digital spiking neural networks Yuya Oishi, Hiroaki Uchida, Tosimichi Saito (Hosei Univ.) CCS2018-47 |
This paper studies dynamics of a network of digital spiking neurons. Repeating integrate-and-fire behavior between a p... [more] |
CCS2018-47 pp.7-10 |
| MBE, NC, NLP (Joint) |
2018-01-27 14:25 |
Fukuoka | Kyushu Institute of Technology | A study on FPGA implementation of SAM spiking neural network Minoru Motoki, Kazunori Matsuo, Hirohito Shintani (NIT, Kumamoto Col.) NC2017-65 |
his paper describes a design for FPGA implementation of SAM spiking neural network and experimental results of circuit r... [more] | NC2017-65 pp.89-94 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2017-06-24 10:20 |
Okinawa | Okinawa Institute of Science and Technology | Synchronization and stability of digital spiking neurons Hiroaki Uchida, Tomoki Hamaguchi, Toshimichi Saito (Hosei Univ.) NC2017-15 |
The digital spiking neuron(DSN) is constructed by two shift-resistors connected by a wiring. Depending on the wiring pat... [more] | NC2017-15 pp.105-108 |
| NLP | 2016-09-15 13:50 |
Hyogo | Konan Univ. | Analysis of Super-stable Periodic Orbits in Piecewise Linear Bifurcating Neuron Circuits Risa Takahashi, Toshimichi Saito (Hosei Univ.) NLP2016-60 |
This paper studies dynamics of the bifurcating neuron circuit. Repeating integrate-and-fire behavior between a constan... [more] |
NLP2016-60 pp.83-87 |
| MBE, NC (Joint) |
2015-11-21 13:25 |
Miyagi | Tohoku University | Steady State Analysis of Digital Spike Maps Hiroki Yamaoka, Toshimichi Saito (Hosei Univ.) NC2015-41 |
This paper studies dynamic of digital spike maps: simple digital dynamical systems that can generate various periodic s... [more] |
NC2015-41 pp.25-29 |
| NLP, CAS | 2015-10-05 13:55 |
Hiroshima | Aster Plaza | Generation of disital spike-trains based on growing greedy search Kei Yamaoka, Toshimichi Saito (HU) CAS2015-27 NLP2015-88 |
This paper studies a simple evolutionary algorithm for synthesis of digital spiking neurons(DSNs). The DSN is based on... [more] |
CAS2015-27 NLP2015-88 pp.37-41 |
| NLP | 2015-04-24 11:15 |
Kagawa | Kagawa Social Welfare Center | Analysis of the Bifurcating Neuron with Two Triangular Base Signal Inputs Risa Takahashi, Yusaku Yanase, Toshimichi Saito (Hosei Univ.) NLP2015-17 |
This paper studies dynamics of the bifurcating neuron with two periodic base signal inputs. The first input is triangula... [more] | NLP2015-17 pp.77-80 |
| MBE, NC (Joint) |
2014-12-13 13:00 |
Aichi | Nagoya University | Analysis of Digital Spike-Maps based on the Feature Quantity Plane Hiroki Yamaoka, Toshimichi Saito (Hosei Univ.) NC2014-50 |
This paper studies dynamic of digital spike maps: simple digital dynamical systems that can generate various periodic s... [more] |
NC2014-50 pp.37-42 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2014-06-26 15:25 |
Okinawa | Okinawa Institute of Science and Technology | Digital Spike-Phase Maps and Bifurcating Neuron with Double Inputs Hiroki Yamaoka, Toshimichi Saito (Hosei Univ.) NC2014-6 IBISML2014-6 |
This paper studies the degital spike phase maps that can generate various spike-trains. In order to consider the stead... [more] |
NC2014-6 IBISML2014-6 pp.97-100 |
| NLP | 2014-03-11 13:55 |
Tokyo | Sophia University | Digital Spike Maps based on the Bifurcating Neurons Hiroki Yamaoka, Narutoshi Horimoto, Toshimichi Saito (Hosei Univ.) NLP2013-184 |
This paper studies basic dynamics of a digital spike-phase map from a set of lattice points to itself. Depending on para... [more] | NLP2013-184 pp.111-115 |
| NC, MBE (Joint) |
2013-12-21 14:20 |
Gifu | Gifu University | Response of Simple Bifurcating neurons to plural inputs Yusaku Yanase, Shota Kirikawa, Toshimichi Saito (HU) NC2013-63 |
This paper studies a simple spiking neuron model with double inputs. The double inputs are applied as the base signal fo... [more] | NC2013-63 pp.59-62 |
| NLP | 2013-10-29 13:15 |
Kagawa | Sanport Hall Takamatsu | Basic Classification of Dynamics from Digital Spike Maps Toshimichi Saito, Narutoshi Horimoto (Hosei Univ.) NLP2013-99 |
This paper studies various transient- and steady-state spike-trains generated by the digital spike map: a simple digital... [more] | NLP2013-99 pp.153-157 |
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