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Lagged multi-affine height correlation analysis for exploring lagged correlations in complex systems

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成果类型:
期刊论文
作者:
Wang, Fang*;Wang, Lin;Chen, Yuming
通讯作者:
Wang, Fang
作者机构:
[Wang, Fang] Hunan Agr Univ, Coll Sci, Agr Math Modeling & Data Proc Ctr, Changsha 410128, Hunan, Peoples R China.
[Wang, Lin] Univ New Brunswick, Dept Math & Stat, Fredericton, NB E3B 5A3, Canada.
[Chen, Yuming] Wilfrid Laurier Univ, Dept Math, Waterloo, ON N2L 3C5, Canada.
通讯机构:
[Wang, Fang] H
Hunan Agr Univ, Coll Sci, Agr Math Modeling & Data Proc Ctr, Changsha 410128, Hunan, Peoples R China.
语种:
英文
期刊:
CHAOS
ISSN:
1054-1500
年:
2018
卷:
28
期:
6
页码:
061102
基金类别:
National Natural Science Foundation of China#&#&#31501227 Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
机构署名:
本校为第一且通讯机构
院系归属:
理学院
摘要:
In order to analyze lagged correlations hidden in complex systems, we propose a new method by incorporating a time-lagged operator into the multi-affine height correlation analysis (MA-HCA). Application of this lagged MA-HCA to an artificially simulated example indicates that the method is feasible to successfully detect the existence of lagged correlations. We then apply this method to explore lagged correlations in ser...

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