Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks (2018)
Source: Frontiers in Computational Neuroscience. Unidade: FFCLRP
Subjects: REDES COMPLEXAS, REDE NERVOSA, REDES NEURAIS, MODELOS PARA PROCESSOS ESTOCÁSTICOS
ABNT
PENA, Rodrigo Felipe de Oliveira et al. Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks. Frontiers in Computational Neuroscience, v. 12, 2018Tradução . . Disponível em: https://doi.org/10.3389/fncom.2018.00009. Acesso em: 17 ago. 2024.APA
Pena, R. F. de O., Vellmer, S., Bernardi, D., Roque, A. C., & Lindner, B. (2018). Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks. Frontiers in Computational Neuroscience, 12. doi:10.3389/fncom.2018.00009NLM
Pena RF de O, Vellmer S, Bernardi D, Roque AC, Lindner B. Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks [Internet]. Frontiers in Computational Neuroscience. 2018 ; 12[citado 2024 ago. 17 ] Available from: https://doi.org/10.3389/fncom.2018.00009Vancouver
Pena RF de O, Vellmer S, Bernardi D, Roque AC, Lindner B. Self-consistent scheme for spike-train power spectra in heterogeneous sparse networks [Internet]. Frontiers in Computational Neuroscience. 2018 ; 12[citado 2024 ago. 17 ] Available from: https://doi.org/10.3389/fncom.2018.00009