A combined measure to differentiate EEG signals using fractal dimension and MFDFA-Hurst (2020)
David, Sérgio Adriani 
; Machado, José António Tenreiro; Inácio Junior, Cláudio Marcio Cassela; Valentim Junior, Carlos Alberto
Fonte: Communications in Nonlinear Science and Numerical Simulation. Unidade: FZEA
Assuntos: EPILEPSIA, ELETROENCEFALOGRAFIA, MEMÓRIA, DIMENSÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DAVID, Sérgio Adriani et al. A combined measure to differentiate EEG signals using fractal dimension and MFDFA-Hurst. Communications in Nonlinear Science and Numerical Simulation, v. 84, p. 1-13, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.cnsns.2020.105170. Acesso em: 05 nov. 2025.APA
David, S. A., Machado, J. A. T., Inácio Junior, C. M. C., & Valentim Junior, C. A. (2020). A combined measure to differentiate EEG signals using fractal dimension and MFDFA-Hurst. Communications in Nonlinear Science and Numerical Simulation, 84, 1-13. doi:10.1016/j.cnsns.2020.105170NLM
David SA, Machado JAT, Inácio Junior CMC, Valentim Junior CA. A combined measure to differentiate EEG signals using fractal dimension and MFDFA-Hurst [Internet]. Communications in Nonlinear Science and Numerical Simulation. 2020 ; 84 1-13.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1016/j.cnsns.2020.105170Vancouver
David SA, Machado JAT, Inácio Junior CMC, Valentim Junior CA. A combined measure to differentiate EEG signals using fractal dimension and MFDFA-Hurst [Internet]. Communications in Nonlinear Science and Numerical Simulation. 2020 ; 84 1-13.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1016/j.cnsns.2020.105170
