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Chaotic Time Series Prediction of Echo State Network Based on Memristor
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In this paper, we proposed a new echo state network (ESN) model, namely
echo state network based on memristor (memristor-ESN). It improve the
memory function of the reservoir and the prediction performance of the
ESN. In the memristor-ESN, memristor is used to replace the synapses
between neurons in the reservoir of echo state network. In the
prediction of chaotic time series, we compare the classical echo state
network with the echo state network based on memristor. Simulations are
conducted to verify the prediction accuracy and prediction performance
of the memristor-ESN.
Title: Chaotic Time Series Prediction of Echo State Network Based on Memristor
Description:
In this paper, we proposed a new echo state network (ESN) model, namely
echo state network based on memristor (memristor-ESN).
It improve the
memory function of the reservoir and the prediction performance of the
ESN.
In the memristor-ESN, memristor is used to replace the synapses
between neurons in the reservoir of echo state network.
In the
prediction of chaotic time series, we compare the classical echo state
network with the echo state network based on memristor.
Simulations are
conducted to verify the prediction accuracy and prediction performance
of the memristor-ESN.
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