Wavelet-based detection of scaling behavior in noisy experimental data
Abstract
The detection of power-laws in real data is a demanding task for several reasons. The two, more frequently met, being: (i) real data possess noise which affects significantly the power-law tails and (ii) there is no solid tool for the discrimination between a power-law, valid in a specific range of scales, from other functional forms like log-normal or stretched exponential distributions. In the present report we demonstrate, employing simulated...
Paper Details
Title
Wavelet-based detection of scaling behavior in noisy experimental data
Published Date
May 8, 2020
Journal
Volume
101
Issue
5
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