Description
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.
Download count: 0
Details
Contributors
- Jiang, Junjie (Author)
- Huang, Zi-Gang (Author)
- Huang, Liang (Author)
- Liu, Huan (Author)
- Lai, Ying-Cheng (Author)
- Ira A. Fulton Schools of Engineering (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2016-04-12
Resource Type
Collections this item is in
Identifier
- Digital object identifier: 10.1038/srep24088
- Identifier TypeInternational standard serial numberIdentifier Value2045-2322
Note
- The final version of this article, as published in Scientific Reports, can be viewed online at: https://www.nature.com/articles/srep24088, opens in a new window
Citation and reuse
Cite this item
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