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 19
Acoustic signals and their corresponding fractal dimensions (running average with a window width of 201 data points over 20 ms) recorded at 10 kHz against time; SPL: sound pressure level in Pascal; mSPL: SPL multiplied by amplitude multiplier ; (a) fractal dimensions of the acoustic signal calculated from original signals (amplitude multiplier ; ≈ ) with mean values of 27 Hz: 1.377, 35 Hz: 1.394, and 31 Hz: 1.441; (b) fractal dimensions calculated from amplitude multiplier (cf. Figure 18) with mean values of 27 Hz: 1.057, 35 Hz: 1.109, and 31 Hz: 1.348.
