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Inferring connectivity of interacting phase oscillators
Dongchuan Yu1, Luigi Fortuna, Fang Liu
1College of Automation Engineering, Qingdao University, Qingdao, Shandong 266071, China. dongchuanyu@yanehoo.com
Chaos (Woodbury, N.Y.)
|January 7, 2009
Summary
This study presents a novel control-based method to infer network topology from dynamic behavior. The approach identifies network connections by analyzing steady-state responses, applicable to both model-dependent and model-free systems.
Area of Science:
- Complex Systems
- Network Science
- Dynamical Systems
Background:
- Understanding the relationship between network topology and dynamics is crucial.
- Inferring network structure from observed behavior remains a significant challenge.
Purpose of the Study:
- To develop and validate a control-based method for inferring network topology from dynamic evolution.
- To address the inverse problem of network identification.
Main Methods:
- A two-step approach: 1) driving the network to a steady state, 2) inferring the connectivity matrix from node responses.
- Strategies developed for both model-dependent and model-free scenarios.
- Analysis of noise influence on topology identification accuracy.
Main Results:
- Successful inference of network topology is demonstrated under specific conditions for both model-dependent and model-free cases.
- The method's effectiveness is illustrated using networks of phase oscillators.
- Conditions for correct topology identification are detailed.
Conclusions:
- The proposed control-based method effectively infers network topology from dynamics.
- The approach is generalizable to various dynamical networks beyond phase oscillators.
- This work provides a framework for network structure identification from observed behavior.
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