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Filtros : "REDES NEURAIS" "Financiamento DFG" Removido: "Ci" Limpar

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  • Artigo de periodico

    Clustered and deep echo state networks for signal noise reduction (2022)

    Oliveira Junior, Laercio de; Stelzer, Florian; Liang, Zhao

    Source: Machine Learning. Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, REDES NEURAIS, SISTEMAS DINÂMICOS

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • 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: 18 set. 2024.

    • 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 2024 set. 18 ] 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 2024 set. 18 ] Available from: https://doi.org/10.1007/s10994-022-06135-6

  • Artigo de periodico

    Short-term and spike-timing-dependent plasticity facilitate the formation of modular neural networks (2021)

    Lameu, Ewandson Luiz ; Borges, Fernando S.; Iarosz, Kelly ; Protachevicz, R. P. ; Antonopoulos, Chris G. ; Macau, Elbert E.N.; Batista, Antonio

    Source: Communications in Nonlinear Science and Numerical Simulation. Unidade: IF

    Subjects: BIOFÍSICA, REDES NEURAIS, PLASTICIDADE NEURONAL, SINAPSE, NEUROTRANSMISSORES

    Versão PublicadaAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      LAMEU, Ewandson Luiz et al. Short-term and spike-timing-dependent plasticity facilitate the formation of modular neural networks. Communications in Nonlinear Science and Numerical Simulation, v. 96, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.cnsns.2020.105689. Acesso em: 18 set. 2024.

    • APA

      Lameu, E. L., Borges, F. S., Iarosz, K., Protachevicz, R. P., Antonopoulos, C. G., Macau, E. E. N., & Batista, A. (2021). Short-term and spike-timing-dependent plasticity facilitate the formation of modular neural networks. Communications in Nonlinear Science and Numerical Simulation, 96. doi:10.1016/j.cnsns.2020.105689

    • NLM

      Lameu EL, Borges FS, Iarosz K, Protachevicz RP, Antonopoulos CG, Macau EEN, Batista A. Short-term and spike-timing-dependent plasticity facilitate the formation of modular neural networks [Internet]. Communications in Nonlinear Science and Numerical Simulation. 2021 ; 96[citado 2024 set. 18 ] Available from: https://doi.org/10.1016/j.cnsns.2020.105689

    • Vancouver

      Lameu EL, Borges FS, Iarosz K, Protachevicz RP, Antonopoulos CG, Macau EEN, Batista A. Short-term and spike-timing-dependent plasticity facilitate the formation of modular neural networks [Internet]. Communications in Nonlinear Science and Numerical Simulation. 2021 ; 96[citado 2024 set. 18 ] Available from: https://doi.org/10.1016/j.cnsns.2020.105689
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