| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NC, MBE (Joint) |
2024-09-27 15:40 |
Miyagi | Tohoku Univ. (Miyagi, Online) (Primary: On-site, Secondary: Online) |
Analog CMOS circuit implementation of STDP and its application to classification tasks Yosuke Iida, Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ)  NC2024-37 |
STDP, a learning rule suitable for spiking neural networks, learns from local spike timing differences between neurons. ... [more] | NC2024-37 pp.29-32 |
| NC, MBE (Joint) |
2024-09-28 11:10 |
Miyagi | Tohoku Univ. (Miyagi, Online) (Primary: On-site, Secondary: Online) |
Analysis of structure-function relationships in neuronal networks using a Markov chain model Nobuaki Monma, Hideaki Yamamoto, Naoya Fujiwara, Shigeo Sato (Tohoku Univ.) NC2024-40 |
[more] | NC2024-40 pp.41-44 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-22 11:40 |
Okinawa | OIST (Okinawa) | Hierarchical reservoir computing model with circle topology for time series prediction and anomaly detection Wenkai Yu, Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ) NC2024-31 IBISML2024-31 |
Reservoir computing (RC), known for its high resource efficiency and ability to handle dynamic data, is gaining attentio... [more] | NC2024-31 IBISML2024-31 p.188 |
| NC, MBE (Joint) |
2023-10-28 10:45 |
Miyagi | Tohoku Univ. (Miyagi, Online) (Primary: On-site, Secondary: Online) |
A design of ultra-low power reservoir computing system with analog CMOS spiking neural network circuits Satoshi Ono, Satoshi Moriya, Hideaki Yamamoto (Tohoku Univ.), Yasushi Yuminaka (Gunma Univ.), Yoshihiko Horio, Shigeo Sato (Tohoku Univ.) NC2023-29 |
Spiking neural network (SNN) is expected to be applied to edge computing due to its low power consumption when implement... [more] | NC2023-29 p.23 |
| NC, MBE (Joint) |
2023-10-28 11:10 |
Miyagi | Tohoku Univ. (Miyagi, Online) (Primary: On-site, Secondary: Online) |
Multi-step ahead time series prediction based on hierarchical reservoir computing with multiple memory capacity. Wenkai Yu, Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ) NC2023-30 |
Reservoir computing has proven to be an efficient model in many areas, such as time series prediction. However, multi-st... [more] | NC2023-30 p.24 |
| NC, MBE (Joint) |
2022-09-29 10:00 |
Miyagi | Tohoku Univ. (Miyagi, Online) (Primary: On-site, Secondary: Online) |
Fabrication of artificial neuronal networks for analyzing neuronal ensemble functions Hakuba Murota, Hideaki Yamamoto, Takuma Sumi, Shigeo Sato, Ayumi Hirano (Tohoku Univ.) NC2022-32 |
In this study, we applied cell patterning technology using polydimethylsiloxane microfluidics to fabricate artificial ne... [more] | NC2022-32 pp.1-4 |
| NC, MBE (Joint) |
2022-09-29 10:25 |
Miyagi | Tohoku Univ. (Miyagi, Online) (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 |
| SCE | 2022-08-09 13:00 |
Online | Online (Online) | Physical Reservoir using Josephson Transmission Line for Waveform Classification Kohki Watanabe (Tohoku Univ.), Yoshinao Mizugaki (Univ.Electro-Communications), Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ.) SCE2022-6 |
Superconducting device is expected to be applied to machine learning due to its outstanding low power consumption proper... [more] | SCE2022-6 pp.30-33 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-29 13:55 |
Okinawa | (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Optimization of recurrent neural network structure by controlling symmetry of weight matrix Arisa Fujimoto, Hideaki Yamamoto, Satoshi Moriya (Tohoku Univ.), Keita Tokuda (Tsukuba Univ.), Yuichi Katori (Future Univ. Hakodate), Shigeo Sato (Tohoku Univ.) NC2022-26 IBISML2022-26 |
In this study, we investigated the relationship between the strength of symmetry in a Gaussian random matrix of a recurr... [more] | NC2022-26 IBISML2022-26 pp.184-188 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-29 14:20 |
Okinawa | (Okinawa, Online) (Primary: On-site, Secondary: Online) |
LSI implementation of analog CMOS majority circuit for neural network applications Satoshi Ono, Satoshi Moriya, Yuka Kanke, Hideaki Yamamoto (Tohoku Univ.), Yasushi Yuminaka (Gunma Univ.), Shigeo Sato (Tohoku Univ.) NC2022-27 IBISML2022-27 |
Majority logic circuit is a circuit whose output is the majority value of multiple binary inputs. It can be applied to b... [more] | NC2022-27 IBISML2022-27 pp.189-192 |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-23 09:50 |
Online | 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, MICT, MBE, NC (Joint) [detail] |
2022-01-23 10:15 |
Online | Online (Online) | Analog CMOS implementation of majority logic for neuromorphic circuit applications Satoshi Ono, Satoshi Moriya, Yuka Kanke, Hideaki Yamamoto (Tohoku Univ.), Yasushi Yuminaka (Gunma Univ.), Shigeo Sato (Tohoku Univ.) NC2021-41 |
A majority logic circuit is a circuit whose output is the majority value of multiple binary inputs. In addition to its c... [more] | NC2021-41 pp.45-48 |
| MBE, NC (Joint) |
2021-10-28 11:40 |
Online | Online (Online) | Reservoir computing properties of micropatterned neuronal networks in culture Takuma Sumi, Hideaki Yamamoto, Satoshi Moriya, Taiki Takemuro, Tomohiro Konno, Shigeo Sato, Ayumi Hirano-Iwata (Tohoku Univ) NC2021-19 |
In this experiment, we used the reservoir computing model to analyze the information processing properties of micropatte... [more] | NC2021-19 pp.7-10 |
| MBE, NC (Joint) |
2021-10-28 16:20 |
Online | Online (Online) | Study on rounding error and Learning performance of reinforcement learning model for FPGA implementation Daisuke Oguchi, Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ) NC2021-24 |
In recent years, the hardware implementation of reinforcement learning (RL) has attracted attention due to its wide rang... [more] | NC2021-24 pp.34-39 |
| MBE, NC, NLP, CAS (Joint) [detail] |
2020-10-29 15:20 |
Online | 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 |
| NC, MBE (Joint) |
2020-03-06 13:25 |
Tokyo | University of Electro Communications (Tokyo) (Cancelled but technical report was issued) |
Modular Reservoir Network for Pattern Recognition Yifan Dai, Masao Sakuraba, Shigeo Sato (Tohoku Univ.) NC2019-110 |
This work is based on liquid state machine (LSM) [1], which is a reservoir network [2] that yields deep relationship wit... [more] | NC2019-110 p.199 |
| MBE, NC | 2019-10-12 11:45 |
Miyagi | (Miyagi) | LSI Implementation and Its Evaluation of an Izhikevich Model Neuron Analog MOS Circuit Yuki Tamura, Satoshi Moriya, Tatsuki Kato, Masao Sakuraba, Shigeo Sato, Yoshihiko Horio (Tohoku Univ.) MBE2019-44 NC2019-35 |
The Izhikevich neuron model, which can reproduce various spike activities with a small amount of calculation, is indispe... [more] | MBE2019-44 NC2019-35 pp.69-73 |
| NC, MBE (Joint) |
2019-03-04 16:10 |
Tokyo | University of Electro Communications (Tokyo) | Proposal of an Izhikevich Model Neuron MOS Circuit Yuki Tamura, Satoshi Moriya, Tatsuki Kato, Masao Sakuraba, Yoshihiko Horio, Shigeo Sato (Tohoku Univ.) NC2018-60 |
The Izhikevich neuron model, which can reproduce various spike activities with a small amount of calculation, is indispe... [more] | NC2018-60 p.93 |
| NC, MBE (Joint) |
2018-10-19 14:00 |
Miyagi | Tohoku Univ. (Miyagi) | A study on an Izhikevich Model Neuron MOS Circuit Yuki Tamura, Satoshi Moriya, Masao Sakuraba, Shigeo Sato (Tohoku Univ.) NC2018-13 |
The Izhikevich neuron, which can reproduce various spike activities with a small amount of calculation, is indispensable... [more] | NC2018-13 pp.1-5 |
| NC, MBE (Joint) |
2018-10-19 14:25 |
Miyagi | Tohoku Univ. (Miyagi) | Functional complexity in neuronal network models with hierarchically modular organization Zhixiong Chen, Hideaki Yamamoto, Satoshi Moriya, Katsuya Ide (Tohoku Univ.), Shigeru Kubota (Yamagata Univ.), Shigeo Sato, Ayumi Hirano-Iwata (Tohoku Univ.) NC2018-14 |
Research and development of hardware and architectures that imitate the information processing mechanism of brains is be... [more] | NC2018-14 pp.7-12 |
[Return to Top Page]