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Information entropy of diffusion processes on complex networks

机译:复杂网络上扩散过程的信息熵

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摘要

Diffusion processes have been widely investigated to understand some essential features of complex networks, and have attracted much attention from physicists, statisticians and computer scientists. In order to understand the evolution of the diffusion process and design the optimal routing strategy according to the maximal entropic diffusion on networks, we propose the information entropy comprehending the structural characteristics and information propagation on the network. Based on the analysis of the diffusion process, we analyze the coupling impact of the structural factor and information propagating factor on the information entropy, where the analytical results fit well with the numerical ones on scale-free complex networks. The information entropy can better characterize the complex behaviors on networks and provides a new way to deepen the understanding of the diffusion process.
机译:为了了解复杂网络的某些基本特征,已经广泛地研究了扩散过程,并且引起了物理学家,统计学家和计算机科学家的广泛关注。为了了解扩散过程的演变过程,并根据最大熵在网络上的扩散来设计最优路由策略,我们提出了一种信息熵,该信息熵应包含网络的结构特征和信息传播。在分析扩散过程的基础上,我们分析了结构因素和信息传播因素对信息熵的耦合影响,分析结果与无标度复杂网络上的数值结果吻合良好。信息熵可以更好地刻画网络上的复杂行为,并为加深对扩散过程的理解提供了新的途径。

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