Abstract
Improvement in time resolution sometimes introduces fast (short-range) random noises into temporal data sequences. These noises affect the results of power-spectrum analyses and the detrended fluctuation analysis (DFA). The DFA is one of useful methods for analyzing long-range correlations in non-stationary sequences. The effects of noises are discussed based on artificial temporal sequences. Short-range noises prevent power-spectrum analyses from detecting long-range correlations. The DFA can extract long-range correlations from noisy time sequences. The DFA also gives the threshold time length, under which the noises dominate.
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