2016
DOI: 10.1088/1742-5468/2016/03/033206
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Multifractality and Laplace spectrum of horizontal visibility graphs constructed from fractional Brownian motions

Abstract: Many studies have shown that additional information can be gained on time series by investigating their associated complex networks. In this work, we investigate the multifractal property and Laplace spectrum of the horizontal visibility graphs (HVGs) constructed from fractional Brownian motions. We aim to identify via simulation and curve fitting the form of these properties in terms of the Hurst index H. First, we use the sandbox algorithm to study the multifractality of these HVGs. It is found that multifra… Show more

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Cited by 18 publications
(14 citation statements)
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“…The tool of multifractal analysis has been widely used in many fields, including biological systems [30][31][32][33] and geophysical data analyses [34][35][36][37]. Many recent studies have shown that multifractal analysis performs well in characterizing the complexity of complex networks [24][25][26][27][38][39][40][41][42][43][44][45][46]. Furuya et al [39] pointed out that multifractal structures exist in some deterministic model networks, stochastic model networks, and real-world scale-free networks.…”
Section: J Stat Mech (2019) 073405mentioning
confidence: 99%
See 1 more Smart Citation
“…The tool of multifractal analysis has been widely used in many fields, including biological systems [30][31][32][33] and geophysical data analyses [34][35][36][37]. Many recent studies have shown that multifractal analysis performs well in characterizing the complexity of complex networks [24][25][26][27][38][39][40][41][42][43][44][45][46]. Furuya et al [39] pointed out that multifractal structures exist in some deterministic model networks, stochastic model networks, and real-world scale-free networks.…”
Section: J Stat Mech (2019) 073405mentioning
confidence: 99%
“…Xue and Bogdan [41] presented a reliable multifractal analysis for some weighted complex networks. Our group has also performed some studies on complex networks by calculating their generalized fractal dimensions D(q) and then exploring their multifractality [24][25][26][27][43][44][45][46] . In particular, we proposed a modified sandbox algorithm [44] which can very eectively https://doi.org/10.1088/1742-5468/ab2906 J. Stat.…”
Section: J Stat Mech (2019) 073405mentioning
confidence: 99%
“…Network multifractal analysis is an extension of the fractal analysis that allows the study of the complexity of the network structure by considering different fractal scaling exponents in different regions of the network. [19] Furuya and Yakubo [20] performed multifractal analysis of the network using an improved compactboxburning algorithm in the study of Song et al [18] Meanwhile, Wang et al [21] proposed the box-covering algorithm and used the algorithm to calculate the generalized fractal dimensions of theoretical networks and real networks. Immediately following, Liu et al [22] adapted the Sandbox algorithm [23] for signal fractal analysis to multifractals of complex networks with a lower time complexity compared to previous algorithms.…”
Section: Introductionmentioning
confidence: 99%
“…Song et al [30] developed a method for calculating the fractal dimension of a complex network by using a box-covering algorithm and identified self-similarity as a property of complex networks [31]. Moreover, a myriad of algorithms and studies on networks' multifractal analysis have been proposed and developed lately [32][33][34][35][36][37].…”
Section: Introductionmentioning
confidence: 99%