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题名: Analyzing long-term correlated stochastic processes by means of recurrence networks: Potentials and pitfalls
作者: Zou, Y;  Donner, RV;  Kurths, J
刊名: PHYSICAL REVIEW E
出版日期: 2015
卷号: 91, 期号:2, 页码:22926
学科分类: Physics
DOI: http://dx.doi.org/10.1103/PhysRevE.91.022926
通讯作者: Zou, Y (reprint author), E China Normal Univ, Dept Phys, Shanghai 200062, Peoples R China.
文章类型: Article
英文摘要: Long-range correlated processes are ubiquitous, ranging from climate variables to financial time series. One paradigmatic example for such processes is fractional Brownian motion (fBm). In this work, we highlight the potentials and conceptual as well as practical limitations when applying the recently proposed recurrence network (RN) approach to fBm and related stochastic processes. In particular, we demonstrate that the results of a previous application of RN analysis to fBm [Liu et al., Phys. Rev. E 89, 032814 (2014)] are mainly due to an inappropriate treatment disregarding the intrinsic nonstationarity of such processes. Complementarily, we analyze some RN properties of the closely related stationary fractional Gaussian noise (fGn) processes and find that the resulting network properties are well-defined and behave as one would expect from basic conceptual considerations. Our results demonstrate that RN analysis can indeed provide meaningful results for stationary stochastic processes, given a proper selection of its intrinsic methodological parameters, whereas it is prone to fail to uniquely retrieve RN properties for nonstationary stochastic processes like fBm.
类目[WOS]: Physics, Fluids & Plasmas ;  Physics, Mathematical
关键词[WOS]: DETRENDED FLUCTUATION ANALYSIS ;  TIME-SERIES ;  STRANGE ATTRACTORS ;  SYSTEMS ;  TRANSITIONS ;  PERSISTENCE ;  DIMENSION ;  EVOLUTION ;  PLOTS
收录类别: SCI
项目资助者: NNSF of China [11305062, 11135001, 81471651] ;  Specialized Research Fund (SRF) for the Doctoral Program [20130076120003] ;  SRF for ROCS, SEM ;  Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y4KF151CJ1] ;  German Academic Exchange Service (DAAD) ;  German Federal Ministry for Education and Research (BMBF) [01LN1306A]
语种: 英语
Citation statistics: 
内容类型: 期刊论文
URI标识: http://ir.itp.ac.cn/handle/311006/21082
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Recommended Citation:
Zou, Y,Donner, RV,Kurths, J. Analyzing long-term correlated stochastic processes by means of recurrence networks: Potentials and pitfalls[J]. PHYSICAL REVIEW E,2015,91(2):22926.
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