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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

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.

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    Title
    • Directed Dynamical Influence is More Detectable With Noise
    Contributors
    Date Created
    2016-04-12
    Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.1038/srep24088
    • Identifier Type
      International standard serial number
      Identifier Value
      2045-2322
    Note
    • The final version of this article, as published in Scientific Reports, can be viewed online at: https://www.nature.com/articles/srep24088

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    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Jiang, J., Huang, Z., Huang, L., Liu, H., & Lai, Y. (2016). Directed dynamical influence is more detectable with noise. Scientific Reports, 6(1). doi:10.1038/srep24088

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