文章基本信息

标题：Estimating the minimum control count of random network models
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作者：Derek Ruths ; Justin Ruths
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2016
卷号：6
期号：1
DOI：10.1038/srep19818
语种：English
出版社：Springer Nature
摘要：The study of controllability of complex networks has introduced the minimum number of controls required for full controllability as a new network measure of interest. This network measure, like many others, is non-trivial to compute. As a result, establishing the significance of minimum control counts (MCCs) in real networks using random network null models is expensive. Here we derive analytic estimates for the expected MCCs of networks drawn from three commonly-used random network models. Our estimates show good agreement with exact control counts. Furthermore, the analytic expressions we derive offer insights into the structures within each random network model that induce the need for controls.