It has been found that the structure of complex network has significant influence on the condensation of particles and the equilibrium state of particles is dynamical. We study here the fluctuation of particles on each individual node at equilibrium status and find that the particle distributions ca
Effect of coarse-graining on detrended fluctuation analysis
β Scribed by Radhakrishnan Nagarajan
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Weight
- 649 KB
- Volume
- 363
- Category
- Article
- ISSN
- 0378-4371
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β¦ Synopsis
Several studies have investigated the scaling behavior in naturally occurring biological and physical processes using techniques such as detrended fluctuation analysis (DFA). Data acquisition is an inherent part of these studies and maps the continuous process into digital data. The resulting digital data is discretized in amplitude and time, and shall be referred to as coarse-grained realization in the present study. Since coarse-graining precedes scaling exponent analysis, it is important to understand its effects on scaling exponent estimators such as DFA. In this brief communication, k-means clustering is used to generate coarse-grained realizations of data sets with different correlation properties, namely: anti-correlated noise, long-range correlated noise and uncorrelated noise. It is shown that the coarse-graining can significantly affect the scaling exponent estimates. It is also shown that scaling exponent can be reliably estimated even at low levels of coarse-graining and the number of the clusters required varies across the data sets with different correlation properties.
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