NDLI: Directed dynamical influence is more detectable with noise

Content Provider	PubMed Central
Author	Jiang, Jun-jie Huang, Zi-gang Huang, Liang Liu, Huan Lai, Ying-cheng
Copyright Year	2016
Abstract	Successful identification of directed dynamical influence in complex systems is relevant to significant problems of current interest. Traditional methods based on Granger causality and transfer entropy have issues such as difficulty with nonlinearity and large data requirement. Recently a framework based on nonlinear dynamical analysis was proposed to overcome these difficulties. We find, surprisingly, that noise can counterintuitively enhance the detectability of directed dynamical influence. In fact, intentionally injecting a proper amount of asymmetric noise into the available time series has the unexpected benefit of dramatically increasing confidence in ascertaining the directed dynamical influence in the underlying system. This result is established based on both real data and model time series from nonlinear ecosystems. We develop a physical understanding of the beneficial role of noise in enhancing detection of directed dynamical influence.
Related Links	http://dx.doi.org/10.1038/srep24088
Starting Page	24088
File Format	PDF
ISSN	20452322
e-ISSN	20452322
Journal	Scientific Reports
Volume Number	6
Language	English
Publisher	Nature Publishing Group
Publisher Date	2016-04-12
Access Restriction	Open
Rights Holder	Nature Publishing Group
Subject Keyword	Science and technology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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Directed dynamical influence is more detectable with noise