中文

Modular networks emerge from multiconstraint optimization

物理与社会 2007-11-05 v2 无序系统与神经网络

摘要

Modular structure is ubiquitous among complex networks. We note that most such systems are subject to multiple structural and functional constraints, e.g., minimizing the average path length and the total number of links, while maximizing robustness against perturbations in node activity. We show that the optimal networks satisfying these three constraints are characterized by the existence of multiple subnetworks (modules) sparsely connected to each other. In addition, these modules have distinct hubs, resulting in an overall heterogeneous degree distribution.

关键词

引用

@article{arxiv.physics/0703033,
  title  = {Modular networks emerge from multiconstraint optimization},
  author = {Raj Kumar Pan and Sitabhra Sinha},
  journal= {arXiv preprint arXiv:physics/0703033},
  year   = {2007}
}

备注

5 pages, 4 figures; Published version