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Updated: Jun 24, 2026

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
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Published on: July 21, 2021

Enhanced synchronizability in scale-free networks.

Maoyin Chen1, Yun Shang, Changsong Zhou

  • 1Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China.

Chaos (Woodbury, N.Y.)
|April 2, 2009
PubMed
Summary
This summary is machine-generated.

We developed a new dynamical optimization coupling scheme to improve synchronization in scale-free networks. This method enhances network synchronizability and allows for larger network sizes compared to unweighted networks.

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Area of Science:

  • Complex networks
  • Network science
  • Dynamical systems

Background:

  • Synchronization is a fundamental phenomenon in complex systems.
  • Scale-free networks exhibit unique structural properties influencing their dynamics.
  • Enhancing synchronizability in large networks remains a challenge.

Purpose of the Study:

  • To introduce a modified dynamical optimization coupling scheme.
  • To enhance the synchronizability of scale-free networks.
  • To maintain uniform and converging intensities during synchronization transitions.

Main Methods:

  • Development of a modified dynamical optimization coupling scheme.
  • Analysis of synchronization properties in scale-free networks.
  • Comparison with unweighted network synchronization capabilities.

Main Results:

  • The proposed scheme significantly enhances network synchronizability.
  • Uniform and converging intensity dynamics were observed during synchronization.
  • Synchronizable network sizes were extended by several orders of magnitude compared to unweighted networks.

Conclusions:

  • The modified dynamical optimization coupling scheme is effective for improving synchronization in scale-free networks.
  • This approach enables synchronization in significantly larger networks.
  • The method offers a robust way to control network dynamics towards synchronization.