摘要翻译：
本文讨论了动力系统网络拓扑结构的重构问题。定义了一个距离函数来评价两个过程的“紧密性”，并导出了一些有用的数学性质。并给出了保证具有树型拓扑结构的网络线性系统辨识过程正确性的理论结果。最后，给出了该方法在实际复杂网络分析中的应用，即对股票市场高频时间序列的分析。
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英文标题：
《Topological identification in networks of dynamical systems》
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作者：
Donatello W. Materassi and Giacomo W. Innocenti
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最新提交年份：
2008
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分类信息：

一级分类：Physics        物理学
二级分类：Chaotic Dynamics        混沌动力学
分类描述：Dynamical systems, chaos, quantum chaos, topological dynamics, cycle expansions, turbulence, propagation
动力系统，混沌，量子混沌，拓扑动力学，循环展开，湍流，传播
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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要：
  The paper deals with the problem of reconstructing the topological structure of a network of dynamical systems. A distance function is defined in order to evaluate the "closeness" of two processes and a few useful mathematical properties are derived. Theoretical results to guarantee the correctness of the identification procedure for networked linear systems with tree topology are provided as well. Finally, the application of the techniques to the analysis of an actual complex network, i.e. to high frequency time series of the stock market, is illustrated.
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PDF链接：
https://arxiv.org/pdf/0804.2441