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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLP, CCS | 2024-06-07 11:20 |
Fukuoka | West Japan General Exhibition Center AIM | Development of a processing hardware for a swarm intelligence algorithm based on spiking-neural oscillator networks Tomoyuki Sasaki (SIT), Hidehiro Nakano (TCU)  NLP2024-33 CCS2024-20 |
(To be available after the conference date) [more] | NLP2024-33 CCS2024-20 pp.84-89 |
| NC, MBE, NLP, MICT (Joint) [detail] |
2024-01-25 11:50 |
Tokushima | Naruto University of Education | Optimization of synaptic scaling rule, its implementation on modular spiking neural networks and analysis of its affects Takumi Shinkawa, Hideyuki Kato (Oita Univ.), Yoshitaka Ishikawa (FUN), Takuma Sumi, Hideaki Yamamoto (Tohoku Univ.), Yuichi Katori (FUN) NLP2023-107 MICT2023-62 MBE2023-53 |
In this study, to theoretically investigate the information processing mechanisms in the brain, we optimized synaptic sc... [more] | NLP2023-107 MICT2023-62 MBE2023-53 pp.110-113 |
| CCS | 2023-11-12 10:25 |
Toyama | Toyama Prefectural University | Analysis of a simple network topology for optimizer based on spiking-neural oscillator networks Tomoyuki Sasaki (SIT), Hidehiro Nakano (TCU) CCS2023-34 |
Optimizer based on Spiking Neural-oscillator Networks (OSNNs) are one of the deterministic PSO methods, which are based ... [more] | CCS2023-34 pp.53-57 |
| NLP | 2023-05-13 10:00 |
Fukushima | Kenshin Koriyama Cultural Center (Koriyama, Fukushima) | A Study of Ergodic Sequential Circuit Neuronal Networks for Use in Neuroprosthetic Devices Yuta Shiomi, Hiroyuki Torikai (Hosei Univ.) NLP2023-1 |
In this study, we propose a network based on an ergodic ordered circuit neuron model. We show that the proposed model c... [more] |
NLP2023-1 pp.1-4 |
| CCS | 2023-03-26 16:05 |
Hokkaido | RUSUTSU RESORT | Simple Applications of WiBIC with Asynchronous Pulse Code Multiple Access Jiaying Lin, Ryuji Nagazawa, Kien Nguyen (Chiba Univ.), Hiroyuki Torikai (Hosei Univ.), Mikio Hasegawa (Tokyo Univ.), Won-Joo Hwang (Pusan National Univ.), Hiroo Sekiya (Chiba Univ.) CCS2022-78 |
In this study, we propose to combine Spiking Neural Network and IoT network to construct a distributed information proce... [more] | CCS2022-78 pp.85-90 |
| 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 | 2022-12-03 15:50 |
Osaka | Osaka Electro-Communication University | A RISC-V Soft-core Processor with Custom VLIW Extension for Spiking Neural Network Accelerator Mingyang Li, Yuki Hayashida (Mie Univ.) MBE2022-40 NC2022-62 |
We aim to develop an embedded accelerator for spiking neural networks (SNN). In order to develop prototypes of various S... [more] | MBE2022-40 NC2022-62 pp.86-91 |
| CCS | 2022-11-18 16:00 |
Mie | (Primary: On-site, Secondary: Online) |
Investigation for the coupling interactions in swarm intelligence algorithm based on spiking neural-oscillator networks Tomoyuki Sasaki (SIT), Hidehiro Nakano (TCU) CCS2022-60 |
Optimizer based on Spiking Neural-oscillator Networks (OSNNs) are deterministic swarm intelligence algorithms which intr... [more] | CCS2022-60 pp.85-90 |
| NC, MBE (Joint) |
2022-09-29 10:25 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
Analog circuit implementation of spiking neural networks and its application to time-series information processing Satoshi Moriya, Hideaki Yamamoto (Tohoku Univ), Yasushi Yuminaka (Gunma Univ.), Shigeo Sato, Yoshihiko Horio (Tohoku Univ) NC2022-33 |
Edge computing in which low-dimensional signals such as sensor output are processed nearby sensors have become increasin... [more] | NC2022-33 p.5 |
| NC, MBE (Joint) |
2022-09-29 10:50 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
Improvement of AdaBoost algorithm for spiking neural networks Masaya Kawaguchi, Jun Ohkubo (Saitama Univ.) NC2022-34 |
Unlike artificial neural networks (ANNs), which have been widely used recently, spiking neural networks (SNNs) have attr... [more] | NC2022-34 pp.6-10 |
| CCS, NLP | 2022-06-09 15:45 |
Osaka | (Primary: On-site, Secondary: Online) |
Reservoir computing with spiking neural networks and reward-modulated STDP Takayuki Tsurumi, Gouhei Tanaka (UTokyo) NLP2022-7 CCS2022-7 |
In a previous study, it was verified that tasks requiring nonlinearity and working memory can be performed using reward-... [more] | NLP2022-7 CCS2022-7 pp.31-35 |
| CCS, NLP | 2022-06-10 15:55 |
Osaka | (Primary: On-site, Secondary: Online) |
Swarm intelligence algorithm based on spiking neural-oscillator networks, coupling interactions and solving performances Tomoyuki Sasaki (SIT), Hidehiro Nakano (TCU) NLP2022-22 CCS2022-22 |
Optimizer based on spiking neural-oscillator networks (OSNN) are one of the deterministic swarm intelligence algorithms... [more] |
NLP2022-22 CCS2022-22 pp.111-116 |
| SR | 2022-05-13 13:30 |
Tokyo | NICT Koganei (Primary: On-site, Secondary: Online) |
[Invited Talk]
Computation with optical parametric oscillator networks Hiroki Takesue, Takahiro Inagaki, Kensuke Inaba, Takuya Ikuta, Yasuhiro Yamada, Yuya Yonezu, Toshimori Honjo (NTT) SR2022-15 |
We present our recent effort to realize computations that efficiently solve difficult problems such as combinatorial opt... [more] | SR2022-15 pp.67-69 |
| MSS, NLP | 2022-03-29 09:40 |
Online | Online | Effects of sparse connections in spiking neural networks for unsupervised pattern recognition Hiroki Shinagawa, Kantaro Fujiwara, Gouhei Tanaka (Univ. of Tokyo) MSS2021-69 NLP2021-140 |
Recently, the spiking neural network (SNN) models, which compute using spatio-temporal information representation by neu... [more] | MSS2021-69 NLP2021-140 pp.71-76 |
| VLD, HWS [detail] | 2022-03-07 15:05 |
Online | Online | Low-Energy and Fast Inference Method for Spiking Neural Networks Using Dynamic Threshold Adjustment Takehiro Habara, Hiromitsu Awano (Kyoto Univ.) VLD2021-87 HWS2021-64 |
Conventional SNNs have fixed thresholds that determine the possibility of neuron firing, resulting in degradation of inf... [more] | VLD2021-87 HWS2021-64 pp.57-62 |
| 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 |
| RECONF, VLD, CPSY, IPSJ-ARC, IPSJ-SLDM [detail] | 2022-01-24 17:10 |
Online | Online | Ternarizing Deep Spiking Neural Network Man Wu, Yirong Kan, Van_Tinh Nguyen, Renyuan Zhang, Yasuhiko Nakashima (NAIST) VLD2021-61 CPSY2021-30 RECONF2021-69 |
The feasibility of ternarizing spiking neural networks (SNNs) is studied in this work toward trading a slight accuracy f... [more] | VLD2021-61 CPSY2021-30 RECONF2021-69 pp.67-72 |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-23 09:50 |
Online | Online | Analog-circuit design of STDP learning rule with linear decay and its LSI implementation Satoshi Moriya, Tatsuki Kato (Tohoku Univ.), Yasushi Yuminaka (Gunma Univ.), Hideaki Yamamoto, Shigeo Sato, Yoshihiko Horio (Tohoku Univ.) NC2021-40 |
Spiking neural networks (SNNs) are expected to be the next generation of information processing technology to reduce the... [more] | NC2021-40 p.44 |
| NLP | 2021-12-17 10:00 |
Oita | J:COM Horuto Hall OITA | Basic performances of a swarm intelligence algorithm based on spiking oscillator networks Tomoyuki Sasaki (SIT), Hidehiro Nakano (TCU) NLP2021-43 |
Spiking oscillator networks are simply coupling systems of plural spiking oscillators, which generate various synchroniz... [more] | NLP2021-43 pp.1-6 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2021-12-02 09:20 |
Online | Online | Development of Spiking Neural Network with Mem Capacitor
-- Reduction of recognition accuracy loss by improving the conversion method between synaptic strength and capacitance -- Atsushi Sawada, Reon Oshio, Mutsumi Kimura, Renyuan Zhang, Yasuhiko Nakashima (NAIST) VLD2021-32 ICD2021-42 DC2021-38 RECONF2021-40 |
Research on artificial intelligence is developing rapidly, and there is an increasing need for the development of comput... [more] | VLD2021-32 ICD2021-42 DC2021-38 RECONF2021-40 pp.87-92 |
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