Research Article

A Robust Algorithm for Optimisation and Customisation of Fractal Dimensions of Time Series Modified by Nonlinearly Scaling Their Time Derivatives: Mathematical Theory and Practical Applications

Figure 13

EEG signal recorded at 256 Hz against time (bottom subfigure); the two arrows refer to the time data with the lowest and highest used for determining the amplitude spectrum of Figure 12; top subfigure: fractal dimension (running average with a window width of 255 data points over 1 s) of the EEG signal calculated for different amplitude multipliers (cf. Figure 12).
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