相关突发行为的普遍特征
Universal features of correlated bursty behaviour
摘要：
不均匀的时间过程，如人类通信中出现的那些，神经元尖峰序列，地震信号，包括高活动的突发间隔与长时间的低活动周期交替。在最近的研究中，这种突发行为的特点是一个厚尾事件间的时间分布，而时间相关性的自相关函数测量。然而，这些特征函数不能完全表征时间相关的异质行为。在这里，我们表明，在突发期间的事件数量的分布作为一个很好的指标的依赖关系，导致普遍观察幂律分布在广泛的一类现象。我们发现，在这些完全不同的系统中的相关性通常可以解释的记忆效应和描述的一个简单的唯象模型，它显示的时间行为定性类似于在真实系统中。
英文摘要：
Inhomogeneous temporal processes, like those appearing in human communications, neuron spike trains, and seismic signals, consist of high-activity bursty intervals alternating with long low-activity periods. In recent studies such bursty behavior has been characterized by a fat-tailed inter-event time distribution, while temporal correlations were measured by the autocorrelation function. However, these characteristic functions are not capable to fully characterize temporally correlated heterogenous behavior. Here we show that the distribution of the number of events in a bursty period serves as a good indicator of the dependencies, leading to the universal observation of power-law distribution in a broad class of phenomena. We find that the correlations in these quite different systems can be commonly interpreted by memory effects and described by a simple phenomenological model, which displays temporal behavior qualitatively similar to that in real systems.
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