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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| ICD | 2023-04-10 13:20 |
Kanagawa | (Primary: On-site, Secondary: Online) |
[Invited Talk]
Novel scheme of HZO/Si FeFET reservoir computing for speech recognition Eishin Nako, Kasidit Toprasertpong, Ryosho Nakane, Mitsuru Takenaka, Shinichi Takagi (The Univ. of Tokyo)  ICD2023-4 |
We have demonstrated reservoir computing (RC) using HZO/Si ferroelectric gate FETs (FeFETs), which realizes efficient ti... [more] | ICD2023-4 p.9 |
| CCS | 2023-03-26 10:35 |
Hokkaido | RUSUTSU RESORT | Acquisition of physical kinetics of machines by reservoir computing Sena Kojima, Koki Minagawa, Taisei Saito, Tetsuya Asai (Hokkaido Univ.) CCS2022-67 |
This report focuses on an anomaly detection application of a machine’s dynamical system using reservoir computing. We pr... [more] | CCS2022-67 pp.25-30 |
| CCS | 2023-03-26 11:35 |
Hokkaido | RUSUTSU RESORT | A Study on Hardware Architectures of Ensemble Kalman Filters towards High-Speed and Memory-Efficient Online Learning for Reservoir Computing Kota Tamada, Yuki Abe, Kose Yoshida, Tetsuya Asai (Hokkaido Univ) CCS2022-70 |
The objective of this study was to develop a hardware architecture for an ensemble Kalman filter in reservoir computing.... [more] | CCS2022-70 pp.42-47 |
| NLP, MSS | 2023-03-17 13:10 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Periodic Memory and Learning Chaotic Dynamical Systems in Hysteresis Reservoir Computing Tsukasa Saito, Kenya Jin'no (Tokyo City Univ.) MSS2022-100 NLP2022-145 |
Hysteresis Reservoir Computing, which applies a simple hysteresis network to the reservoir layer of reservoir computing,... [more] | MSS2022-100 NLP2022-145 pp.178-181 |
| NLP, MSS | 2023-03-17 16:45 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Enhancement of functionality in Deep Echo State Network by optimizing leak rate Shuichi Inoue, Sou Nobukawa (CIT), Haruhiko Nishimura (UOH), Eiji Watanabe (NIBB), Teijiro Isokawa (UOH) MSS2022-110 NLP2022-155 |
Deep echo state network (Deep-ESN) model consists of multiple reservoir layers, which can respond on layer-specific diff... [more] | MSS2022-110 NLP2022-155 pp.231-236 |
| SDM | 2023-02-07 15:35 |
Tokyo | Tokyo Univ. (Primary: On-site, Secondary: Online) |
[Invited Talk]
Temperature Dependence of Information Processing Performance of Ionic Liquid Type Intelligent Connection Device Masakazu Kobayashi (NAGASE), Hisashi Shima, Yasuhisa Naitoh, Hiroyuki Akinaga (AIST), Dan Sato, Takuma Matsuo, Masaharu Yonezawa, Kentaro Kinoshita (TUS), Toshiyuki Itoh (Toyota Phys. & Chem. Res. Inst.), Toshiki Nokami (Tottori Univ), Yasumitsu Orii (NAGASE) SDM2022-91 |
The amount of the calculation cost of AI training increases exponentially, and this causes an increase in power consumpt... [more] | SDM2022-91 pp.27-32 |
| NC, NLP | 2023-01-29 14:00 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Performance Evaluation of Reservoir Computing in Cultured Neural Systems Using a Spiking Neuron Model Yoshitaka Ishikawa (Future Univ Hakodate), Takumi Shinkawa (Oita Univ), Takuma Sumi (Tohoku Univ), Hideyuki Kato (Oita Univ), Hideaki Yamamoto (Tohoku Univ), Yuichi Katori (Future Univ Hakodate) NLP2022-102 NC2022-86 |
The cultured nervous system can be regarded as a physical reservoir. Intracellular Ca2+ ion concentration is measured fr... [more] | NLP2022-102 NC2022-86 pp.112-117 |
| NC, NLP | 2023-01-29 14:25 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Continuous Value Control of Robot with Reservoir Actor-Critic Model Koutaro Minato, Yuichi Katori (Future Univ Hakodate) NLP2022-103 NC2022-87 |
Deep learning is expected to be utilized to control robots operating in complex environments, but this requires a large ... [more] | NLP2022-103 NC2022-87 pp.118-122 |
| QIT (2nd) |
2022-12-08 17:30 |
Kanagawa | Keio Univ. (Primary: On-site, Secondary: Online) |
Measurement-based Quantum Reservoir Computing Toshiki Yasuda, Yudai Suzuki (Keio), Tomoyuki Kubota, Kohei Nakajima (Tokyo), Caoch (MITSUBISHI CHEMICAL), Hendra Nurdin (UNSW), Naoki Yamamoto (Keio) |
The conventional QRC (Quantum Reservoir Computing) model using a quantum computer has a problem that it lacks nonlineari... [more] | |
| NLP | 2022-11-24 10:20 |
Shiga | (Primary: On-site, Secondary: Online) |
Reconstructing of Vocal Fold Vibration Video by Echo State Network and Dimensionality Reduction Tomu Noguchi, Kota Shiozawa, Isao Tokuda (Ritsumeikan Univ.) NLP2022-56 |
Video data provides an effective means for capturing the dynamics of experimental object. The dimensionality that actual... [more] | NLP2022-56 pp.1-4 |
| NLP | 2022-11-24 16:40 |
Shiga | (Primary: On-site, Secondary: Online) |
Photonic reservoir computing with optical microcavities Kohei Arai, Tomoya Yamaguchi, Tomoaki Niiyama, Satoshi Sunada (Kanazawa Univ.) NLP2022-67 |
Neural networks (NNs), which mimic the function of neural circuits in the brain, use electrons to perform arithmetic ope... [more] | NLP2022-67 pp.43-48 |
| ITE-BCT, OCS, IEE-CMN, OFT | 2022-11-11 13:25 |
Miyagi | Forest-Sendai (Primary: On-site, Secondary: Online) |
Optical nonlinearity compensation using nonlinear equalizer based on complex-valued reservoir computing Kai Ikuta, Jinya Nakamura, Yuta Ito, Moriya Nakamura (Meiji Univ.) OCS2022-45 |
We investigated a nonlinear equalizer based on complex-valued reservoir computing (CVRC) and compared the performance wi... [more] | OCS2022-45 pp.30-35 |
| CAS, NLP | 2022-10-20 16:10 |
Niigata | (Primary: On-site, Secondary: Online) |
Learning Method for Echo State Networks Constructed by Chaotic Neuron Models by Innate Training Yudai Ebato, Sou Nobukawa, Yusuke Sakemi (CIT), Takashi Kanamaru (kougakuin univ), Nina Sviridova (Tokyo Univ. of Science), Kazuyuki Aihara (UTokyo) CAS2022-26 NLP2022-46 |
Echo State Network (ESN) is a machine learning method that consists of an input layer, a layer of recurrent neural netwo... [more] | CAS2022-26 NLP2022-46 pp.35-40 |
| ED, IEE-BMS, IEE-MSS | 2022-08-18 15:20 |
Tokyo | Kikai-Shinko-Kaikan Bldg. B3-2 (Primary: On-site, Secondary: Online) |
Neuromorphic computing using photo-induced current properties in ITO/Nb:SrTiO3 junction
-- For reservoir computing application -- Yutaro Yamazaki, Hiroyuki Kai, Kentaro Kinoshita (Tokyo Univ. of Sci.) ED2022-21 |
Recently, needs for edge computing have been increasing, and methods to reduce computational cost while maintaining high... [more] | ED2022-21 pp.17-20 |
| NLP | 2022-08-02 09:25 |
Online | Online | Performance Evaluation of Time Series Forecasting with Chaotic Neural Network Reservoir using ReLU Derived Functions Tatsuya Saito, Misa Fujita (Chukyo Univ.) NLP2022-27 |
Reservoir computing has been attracting attention in recent years. It can learn time-series data at high speed. Th... [more] |
NLP2022-27 pp.7-10 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-29 13:55 |
Okinawa | (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 15:00 |
Okinawa | (Primary: On-site, Secondary: Online) |
Emergence of Dynamical Orthogonal Basis Acquiring Large Memory Capacity in Modular Reservoir Computing Yuji Kawai (Osaka Univ.), Jihoon Park (NICT/Osaka Univ.), Ichiro Tsuda (Chubu Univ.), Minoru Asada (IPUT/Osaka Univ./Chubu Univ./NICT) NC2022-28 IBISML2022-28 |
The brain's ability to generate complex spatiotemporal patterns with a specific timing is essential for motor learning a... [more] | NC2022-28 IBISML2022-28 pp.193-198 |
| 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 |
| SIS, IPSJ-AVM | 2022-06-10 11:40 |
Fukuoka | KIT(Wakamatsu Campus) (Primary: On-site, Secondary: Online) |
An embedded-oriented sound classification system using reservoir computing Yuichiro Tanaka, Issei Uchino (Kyutech), Kazunobu Ohkuri (Sony), Hakaru Tamukoh (Kyutech) SIS2022-9 |
Although deep neural networks (DNNs) have achieved state-of-the-art results in sound classification tasks in recent year... [more] | SIS2022-9 pp.41-44 |
| SDM, ED, CPM | 2022-05-27 15:50 |
Online | Online | Study on semiconductor-based nonlinear dynamic node for physical reservoir computing system Seiya Kasai, Shunsuke Saito (Hokkaido Univ.) ED2022-12 CPM2022-6 SDM2022-19 |
Reservoir computing is a framework of the neural network-based machine learning for time series. In this system, design ... [more] | ED2022-12 CPM2022-6 SDM2022-19 pp.21-24 |
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