Výsledky vyhledávání - "Nishioka, Daiki"

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A high-performance deep reservoir computing experimentally demonstrated with ion-gating reservoirs

Autor: Nishioka, Daiki, Tsuchiya, Takashi, Imura, Masataka, Koide, Yasuo, Higuchi, Tohru, Terabe, Kazuya

While physical reservoir computing (PRC) is a promising way to achieve low power consumption neuromorphic computing, its computational performance is still insufficient at a practical level. One promising approach to improving PRC performance is deep

Externí odkaz: http://arxiv.org/abs/2309.03028

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Few-molecule reservoir computing experimentally demonstrated with surface enhanced Raman scattering and ion-gating stimulation

Autor: Nishioka, Daiki, Shingaya, Yoshitaka, Tsuchiya, Takashi, Higuchi, Tohru, Terabe, Kazuya

Reservoir computing (RC) is a promising solution for achieving low power consumption neuromorphic computing, although the large volume of the physical reservoirs reported to date has been a serious drawback in their practical application. Here, we re

Externí odkaz: http://arxiv.org/abs/2307.09138

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A Redox-based Ion-Gating Reservoir, Utilizing Double Reservoir States in Drain and Gate Nonlinear Responses

Autor: Wada, Tomoki, Nishioka, Daiki, Namiki, Wataru, Tsuchiya, Takashi, Higuchi, Tohru, Terabe, Kazuya

We have demonstrated physical reservoir computing with a redox-based ion-gating reservoir (redox-IGR) comprising LixWO3 thin film and lithium ion conducting glass ceramic (LICGC). The subject redox-IGR successfully solved a second-order nonlinear dyn

Externí odkaz: http://arxiv.org/abs/2208.06142

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Experimental Demonstration of High-Performance Physical Reservoir Computing with Nonlinear Interfered Spin Wave Multi-Detection

Autor: Namiki, Wataru, Nishioka, Daiki, Yamaguchi, Yu, Tsuchiya, Takashi, Higuchi, Tohru, Terabe, Kazuya

Physical reservoir computing, which is a promising method for the implementation of highly efficient artificial intelligence devices, requires a physical system with nonlinearity, fading memory, and the ability to map in high dimensions. Although it

Externí odkaz: http://arxiv.org/abs/2207.03216

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Edge-Of-Chaos Learning Achieved by Ion-Electron Coupled Dynamics in an Ion-Gating Reservoir

Autor: Nishioka, Daiki, Tsuchiya, Takashi, Namiki, Wataru, Takayanagi, Makoto, Imura, Masataka, Koide, Yasuo, Higuchi, Tohru, Terabe, Kazuya

Physical reservoir computing has recently been attracting attention for its ability to significantly reduce the computational resources required to process time-series data. However, the physical reservoirs that have been reported to date have had in

Externí odkaz: http://arxiv.org/abs/2207.02573

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