Clustered and deep echo state networks for signal noise reduction (2022)
- Authors:
- Autor USP: LIANG, ZHAO - FFCLRP
- Unidade: FFCLRP
- DOI: 10.1007/s10994-022-06135-6
- Subjects: REDES COMPLEXAS; REDES NEURAIS; SISTEMAS DINÂMICOS
- Keywords: Echo state networks; Reservoir computing; Complex networks; Noise reduction
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Machine Learning
- ISSN: 0885-6125
- Volume/Número/Paginação/Ano: v. 111, n. 8, p. 2885-2904, 2022
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
OLIVEIRA JUNIOR, Laercio de e STELZER, Florian e LIANG, Zhao. Clustered and deep echo state networks for signal noise reduction. Machine Learning, v. 111, n. 8, p. 2885-2904, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10994-022-06135-6. Acesso em: 28 fev. 2026. -
APA
Oliveira Junior, L. de, Stelzer, F., & Liang, Z. (2022). Clustered and deep echo state networks for signal noise reduction. Machine Learning, 111( 8), 2885-2904. doi:10.1007/s10994-022-06135-6 -
NLM
Oliveira Junior L de, Stelzer F, Liang Z. Clustered and deep echo state networks for signal noise reduction [Internet]. Machine Learning. 2022 ; 111( 8): 2885-2904.[citado 2026 fev. 28 ] Available from: https://doi.org/10.1007/s10994-022-06135-6 -
Vancouver
Oliveira Junior L de, Stelzer F, Liang Z. Clustered and deep echo state networks for signal noise reduction [Internet]. Machine Learning. 2022 ; 111( 8): 2885-2904.[citado 2026 fev. 28 ] Available from: https://doi.org/10.1007/s10994-022-06135-6 - Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data
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Informações sobre o DOI: 10.1007/s10994-022-06135-6 (Fonte: oaDOI API)
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