Multifractal perturbations to multiplicative cascades promote multifractal nonlinearity with asymmetric spectra

被引:1
|
作者
Mangalam, Madhur [1 ,2 ]
Kelty-Stephen, Damian G. [3 ]
机构
[1] Univ Nebraska Omaha, Dept Biomech, Div Biomech & Res Dev, Omaha, NE 68182 USA
[2] Univ Nebraska Omaha, Ctr Res Human Movement Variabil, Omaha, NE 68182 USA
[3] SUNY Coll New Paltz, Dept Psychol, New Paltz, NY 12561 USA
关键词
DEVELOPMENTAL PROCESSES; PERCEPTION-ACTION; SURROGATE DATA; NOISE; MODELS; NONERGODICITY; IMPROVEMENTS; INFORMATION; PERFORMANCE; FRACTALITY;
D O I
10.1103/PhysRevE.109.064212
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
Biological and psychological processes have been conceptualized as emerging from intricate multiplicative interactions among component processes across various spatial and temporal scales. Among the statistical models employed to approximate these intricate nonlinear interactions across scales, one prominent framework is that of cascades. Despite decades of empirical work using multifractal formalisms, several fundamental questions persist concerning the proper interpretations of multifractal evidence of nonlinear cross-scale interactivity. Does multifractal spectrum width depend on multiplicative interactions, constituent noise processes participating in those interactions, or both? We conducted numerical simulations of cascade time series featuring component noise processes characterizing a range of nonlinear temporal correlations: nonlinearly multifractal, linearly multifractal (obtained via the iterative amplitude adjusted wavelet transform of nonlinearly multifractal), phase-randomized linearity (obtained via the iterative amplitude adjustment Fourier transform of nonlinearly multifractal), and phase and amplitude randomized (obtained via shuffling of nonlinearly multifractal). Our findings show that the multiplicative interactions coordinate with the nonlinear temporal correlations of noise components to dictate emergent multifractal properties. Multiplicative cascades with stronger nonlinear temporal correlations make multifractal spectra more asymmetric with wider left sides. However, when considering multifractal spectral differences between the original and surrogate time series, even multiplicative cascades produce multifractality greater than in surrogate time series, even with linearized multifractal noise components. In contrast, additivity among component processes leads to a linear outcome. These findings provide a robust framework for generating multifractal expectations for biological and psychological models in which cascade dynamics flow from one part of an organism to another.
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页数:26
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