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Filtros : "Communications in Nonlinear Science and Numerical Simulation" "2021" Removido: "IF-FAP" Limpar

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  • Artigo de periodico

    Performance measures after perturbations in the presence of inertia (2021)

    Ye, Jiachen; Peron, Thomas ; Lin, Wei; Kurths, Jürgen; Ji, Peng

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

    Subjects: REDES COMPLEXAS, SISTEMAS DINÂMICOS

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

    • ABNT

      YE, Jiachen et al. Performance measures after perturbations in the presence of inertia. Communications in Nonlinear Science and Numerical Simulation, v. 97, p. 1-10, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.cnsns.2021.105727. Acesso em: 05 nov. 2025.

    • APA

      Ye, J., Peron, T., Lin, W., Kurths, J., & Ji, P. (2021). Performance measures after perturbations in the presence of inertia. Communications in Nonlinear Science and Numerical Simulation, 97, 1-10. doi:10.1016/j.cnsns.2021.105727

    • NLM

      Ye J, Peron T, Lin W, Kurths J, Ji P. Performance measures after perturbations in the presence of inertia [Internet]. Communications in Nonlinear Science and Numerical Simulation. 2021 ; 97 1-10.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1016/j.cnsns.2021.105727

    • Vancouver

      Ye J, Peron T, Lin W, Kurths J, Ji P. Performance measures after perturbations in the presence of inertia [Internet]. Communications in Nonlinear Science and Numerical Simulation. 2021 ; 97 1-10.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1016/j.cnsns.2021.105727

  • 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: 05 nov. 2025.

    • 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 2025 nov. 05 ] 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 2025 nov. 05 ] Available from: https://doi.org/10.1016/j.cnsns.2020.105689
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