Waveform Classification by Two-Layer Reservoir Computing with van der Pol Oscillators

In this research, one van der Pol oscillator is considered as one node, and the oscillators are interconnected using resistors to form a reservoir layer. A networked reservoir computing model which has two layers is proposed (two-layer reservoir). A waveform classification is performed, and the accuracy is compared with a single-layer reservoir. The results show that changing the nature of the oscillator for each layer improves the classification accuracy. This result suggests that using the two-layer reservoir increases design flexibility and improves accuracy.

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Publication Details

Published
2024-08-19
DOI
https://doi.org/10.1109/isocc62682.2024.10762273
Primary Topic
Neural Networks and Reservoir Computing
Type
article
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article

Waveform Classification by Two-Layer Reservoir Computing with van der Pol Oscillators

Yoshifumi Nishio, Yoko Uwate, Yasufumi Kajino
Neural Networks and Reservoir Computing
article

Waveform Classification by Two-Layer Reservoir Computing with van der Pol Oscillators

Yoshifumi Nishio, Yoko Uwate, Yasufumi Kajino
article en

Abstract

In this research, one van der Pol oscillator is considered as one node, and the oscillators are interconnected using resistors to form a reservoir layer. A networked reservoir computing model which has two layers is proposed (two-layer reservoir). A waveform classification is performed, and the accuracy is compared with a single-layer reservoir. The results show that changing the nature of the oscillator for each layer improves the classification accuracy. This result suggests that using the two-layer reservoir increases design flexibility and improves accuracy.

Tokushima University (JP)
Openalex Percentile: Top 80%
Neural Networks and Reservoir Computing
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