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ASU Scholarship Showcase


This growing collection consists of scholarly works authored by ASU-affiliated faculty, students and community members, and contains many open access articles. ASU-affiliated authors are encouraged to Share Your Work in the ASU Digital Repository.


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 …

Contributors
Jiang, Junjie, Huang, Zi-Gang, Huang, Liang, et al.
Created Date
2016-04-12