Reservoir Computing with Pulse-type Hardware Chaotic Neuron Model

Reservoir computing (RC) has attracted much attention in recent years as a model suitable for machine learning of time series information and requiring low computational resources. Among these, physical reservoir computing (PRC), in which RC is implemented in hardware devices, has been actively studied using various devices as it is applicable to edge computing.

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Publication Details

Journal
IEEJ Transactions on Electronics Information and Systems
Published
2025-12-31
DOI
https://doi.org/10.1541/ieejeiss.146.1
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Reservoir Computing with Pulse-type Hardware Chaotic Neuron Model

Katsutoshi Saeki, Takuto Yamaguchi, Takeru Yonekawa
IEEJ Transactions on Electronics Information and Systems
Neural Networks and Reservoir Computing
article

Reservoir Computing with Pulse-type Hardware Chaotic Neuron Model

Katsutoshi Saeki, Takuto Yamaguchi, Takeru Yonekawa
article en

Abstract

Reservoir computing (RC) has attracted much attention in recent years as a model suitable for machine learning of time series information and requiring low computational resources. Among these, physical reservoir computing (PRC), in which RC is implemented in hardware devices, has been actively studied using various devices as it is applicable to edge computing.

IEEJ Transactions on Electronics Information and SystemsVol. 146(1)
Nihon University (JP)
Openalex Percentile: Top 17%
Neural Networks and Reservoir Computing
DOISourceOpenAlex
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Reservoir Computing with Pulse-type Hardware Chaotic Neuron Model — Katsutoshi Saeki, Takuto Yamaguchi, et al. · IEEJ Transactions on Electronics Information and Systems (2025) | TGRS Research Map | TGRS