Extracting complexity waveforms from one-dimensional signals

  title={Extracting complexity waveforms from one-dimensional signals},
  author={A. Kalauzi and Tijana Bojic and Ljubisav Raki{\'c}},
  journal={Nonlinear Biomedical Physics},
  pages={8 - 8}
BACKGROUND Nonlinear methods provide a direct way of estimating complexity of one-dimensional sampled signals through calculation of Higuchi's fractal dimension (1<FD<2). In most cases the signal is treated as being characterized by one value of FD and consequently analyzed as one epoch or, if divided into more epochs, often only mean and standard deviation of epoch FD are calculated. If its complexity variation (or running fractal dimension), FD(t), is to be extracted, a moving window (epoch… CONTINUE READING
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Comparison of fractal dimension oscillations and trends of rainfall data from Pastaza Province, Ecuador and Veneto, Italy

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Climatic trends in the Amazonian area of Ecuador: Classical and multifractal analyses

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The fractal dimension of variations of the solar magnetic field

  • GS Ivanov-Kholodny, EI Mogilevsky, VE Chertoprud
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