Physics – Data Analysis – Statistics and Probability
Scientific paper
2010-01-22
Phys. Rev. Lett. 104, 058701 (2010)
Physics
Data Analysis, Statistics and Probability
2 figures, 2 tables. Accepted by Physical Review Letters
Scientific paper
10.1103/PhysRevLett.104.058701
We study the relationship between dynamical properties and interaction patterns in complex oscillator networks in the presence of noise. A striking finding is that noise leads to a general, one-to-one correspondence between the dynamical correlation and the connections among oscillators for a variety of node dynamics and network structures. The universal finding enables an accurate prediction of the full network topology based solely on measuring the dynamical correlation. The power of the method for network inference is demonstrated by the high success rate in identifying links for distinct dynamics on both model and real-life networks. The method can have potential applications in various fields due to its generality, high accuracy and efficiency.
Lai Ying-Cheng
Li Baowen
Ren Jie
Wang Wen-Xu
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