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Anis Malekzadeh, Assef Zare, Mahdi Yaghoobi and Roohallah Alizadehsani
This paper proposes a new method for epileptic seizure detection in electroencephalography (EEG) signals using nonlinear features based on fractal dimension (FD) and a deep learning (DL) model. Firstly, Bonn and Freiburg datasets were used to perform exp...
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Sílvio Fernando Alves Xavier Júnior, Tatijana Stosic, Borko Stosic, Jader Da Silva Jale, Érika Fialho Morais Xavier (Author)
Pág. e35116
The aim of this study was to evaluate the statistical properties of a daily rainfall time series recorded in Piracicaba river basin, state of Sao Paulo, Brazil in the period 1917-2016. We apply Multifractal Detrended Fluctuation Analysis (MF-DFA) on dese...
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Kai Liu, Xi Zhang and YangQuan Chen
The separation of coal and gangue is an important process of the coal preparation technology. The conventional way of manual selection and separation of gangue from the raw coal can be replaced by computer vision technology. In the literature, research o...
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Alvaro Alberto López-Lambraño,Carlos Fuentes,Alvaro Alberto López-Ramos,Jorge Mata Ramírez,Mariangela López-Lambraño
Pág. 199 - 219
A fractal analysis from rainfall events registered in a semiarid region was carried out. The analysis was executed for Baja California, Mexico, a region that presents a high climatological variability. Rainfall data from 92 climate stations distributed a...
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Erhui Li, Xingmin Mu, Guangju Zhao and Peng Gao
Multifractal detrended fluctuation analysis (MFDFA) can provide information about inner regularity, randomness and long-range correlation of time series, promoting the knowledge of their evolution regularity. The MFDFA are applied to detect long-range co...
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