Online sequential echo state network with sparse RLS algorithm for time series prediction

Recently, the echo state networks (ESNs) have been widely used for time series prediction. To meet the demand of actual applications and avoid the overfitting issue, the online sequential ESN with sparse recursive least squares (OSESN-SRLS) algorithm is proposed. Firstly, the ℓ0 and ℓ1 norm sparsity...

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Vydané v:	Neural networks Ročník 118; s. 32 - 42
Hlavní autori:	Yang, Cuili, Qiao, Junfei, Ahmad, Zohaib, Nie, Kaizhe, Wang, Lei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Ltd 01.10.2019
Predmet:	Algorithms Echo state networks Forecasting Least-Squares Analysis Neural Networks, Computer Online sequential learning Regularization method Sparse recursive least squares algorithm Time Factors Time series prediction Regularization method Online sequential learning Time series prediction Sparse recursive least squares algorithm Echo state networks
ISSN:	0893-6080, 1879-2782, 1879-2782
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