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Zou, Y; Donner, RV; Kurths, J; Zou, Y (reprint author), E China Normal Univ, Dept Phys, Shanghai 200062, Peoples R China.
Analyzing long-term correlated stochastic processes by means of recurrence networks: Potentials and pitfalls
Source PublicationPHYSICAL REVIEW E
Language英语
AbstractLong-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.
2015
Volume91Issue:2Pages:22926
Subject AreaPhysics
DOIhttp://dx.doi.org/10.1103/PhysRevE.91.022926
Indexed BySCI
Funding OrganizationNNSF of China [11305062, 11135001, 81471651] ; NNSF of China [11305062, 11135001, 81471651] ; NNSF of China [11305062, 11135001, 81471651] ; NNSF of China [11305062, 11135001, 81471651] ; Specialized Research Fund (SRF) for the Doctoral Program [20130076120003] ; Specialized Research Fund (SRF) for the Doctoral Program [20130076120003] ; Specialized Research Fund (SRF) for the Doctoral Program [20130076120003] ; Specialized Research Fund (SRF) for the Doctoral Program [20130076120003] ; SRF for ROCS, SEM ; SRF for ROCS, SEM ; SRF for ROCS, SEM ; SRF for ROCS, SEM ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y4KF151CJ1] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y4KF151CJ1] ; Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China [Y4KF151CJ1] ; 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 Academic Exchange Service (DAAD) ; German Academic Exchange Service (DAAD) ; German Academic Exchange Service (DAAD) ; German Federal Ministry for Education and Research (BMBF) [01LN1306A] ; German Federal Ministry for Education and Research (BMBF) [01LN1306A] ; German Federal Ministry for Education and Research (BMBF) [01LN1306A] ; German Federal Ministry for Education and Research (BMBF) [01LN1306A]
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Document Type期刊论文
Identifierhttp://ir.itp.ac.cn/handle/311006/21082
Collection理论物理所科研产出_SCI论文
Corresponding AuthorZou, Y (reprint author), E China Normal Univ, Dept Phys, Shanghai 200062, Peoples R China.
Recommended Citation
GB/T 7714
Zou, Y,Donner, RV,Kurths, J,et al. Analyzing long-term correlated stochastic processes by means of recurrence networks: Potentials and pitfalls[J]. PHYSICAL REVIEW E,2015,91(2):22926.
APA Zou, Y,Donner, RV,Kurths, J,&Zou, Y .(2015).Analyzing long-term correlated stochastic processes by means of recurrence networks: Potentials and pitfalls.PHYSICAL REVIEW E,91(2),22926.
MLA Zou, Y,et al."Analyzing long-term correlated stochastic processes by means of recurrence networks: Potentials and pitfalls".PHYSICAL REVIEW E 91.2(2015):22926.
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