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摘要翻译：
本研究探讨网络结构在LTI系统中的角色与表现。我们证明了传递函数不包含结构信息，而不需要对系统做更多的假设，我们认为这些假设在处理真正复杂的系统时是不合理的。然后，我们引入动态结构函数作为一种替代的、基于图形模型的LTI系统表示，它包含系统的动态和结构信息。我们用动态结构证明了从数据估计网络结构的充要条件，并举例说明了试图用稳态信息估计网络结构的危险性。
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英文标题：
《Dynamical Structure Functions for the Estimation of LTI Networks with
Limited Information》
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作者：
Jorge Goncalves and Sean Warnick
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最新提交年份：
2006
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分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Molecular Networks 分子网络
分类描述：Gene regulation, signal transduction, proteomics, metabolomics, gene and enzymatic networks
基因调控、信号转导、蛋白质组学、代谢组学、基因和酶网络
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一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
This research explores the role and representation of network structure for LTI Systems. We demonstrate that transfer functions contain no structural information without more assumptions being made about the system, assumptions that we believe are unreasonable when dealing with truly complex systems. We then introduce Dynamical Structure Functions as an alternative, graphical-model based representation of LTI systems that contain both dynamical and structural information of the system. We use Dynamical Structure to prove necessary and sufficient conditions for estimating structure from data, and demonstrate, for example, the danger of attempting to use steady-state information to estimate network structure.
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PDF链接：
https://arxiv.org/pdf/q-bio/0610008
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