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Problems of Estimating Fractal Dimension by Higuchi and DFA Methods for Signals That Are a Combination of Fractal and Oscillations

机译:Higuchi和DFA方法估算分形尺寸的问题,即分形和振动组合的信号

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Stochastic fractals of the 1/f noise type are an important manifestation of the brain's electrical activity and other real-world complex systems. Fractal complexity can be successfully estimated by methods such as the Higuchi method and detrended fluctuation analysis (DFA). In this study, we show that if, as with the EEG, the signal is a combination of fractal and oscillation, the estimates of fractal characteristics will be inaccurate. On our test data, DFA overestimated the fractal dimension, while the Higuchi method led to underestimation in the presence of high-amplitude, densely sampled oscillations.
机译:1 / F噪声类型的随机分数是大脑电气活动和其他现实世界复杂系统的重要表现。 可以通过诸如HIGUCHI方法等方法成功估算分形复杂性,并进行了波动分析(DFA)。 在这项研究中,我们表明,如果与脑电图一样,信号是分形和振荡的组合,则分形特征的估计将不准确。 在我们的测试数据中,DFA高估分形尺寸,而HIGUCHI方法导致在高度,密集密集采样振荡的情况下低估。

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