图信号处理基础设施弹性：适用性和未来方向
Graph Signal Processing for Infrastructure Resilience: Suitability and Future Directions
摘要：
图形信号处理（GSP）是一个新兴的领域，用于分析定义在不规则空间结构上的信号。鉴于大量的文献关于基础设施网络的弹性使用图论，这是不足为奇的GSP的一些应用可以在弹性域中找到。GSP技术假定图形傅里叶变换（GFT）的选择赋予感兴趣的信号特定的频谱结构。我们评估了一些配电系统的信号结构的指标，并确定了几个相关的系统属性，并进一步展示了这些指标与性能的一些GSP技术。我们还讨论了数据驱动的方法，提高这些指标的可行性，并将其应用到水分配方案。总的来说，我们发现，许多候选系统分析是正确的结构在所选择的GFT的基础上，并服从GSP技术，但确定相当大的变化和细微差别，值得未来的调查。
英文摘要：
Graph signal processing (GSP) is an emerging field developed for analyzing signals defined on irregular spatial structures modeled as graphs. Given the considerable literature regarding the resilience of infrastructure networks using graph theory, it is not surprising that a number of applications of GSP can be found in the resilience domain. GSP techniques assume that the choice of graphical Fourier transform (GFT) imparts a particular spectral structure on the signal of interest. We assess a number of power distribution systems with respect to metrics of signal structure and identify several correlates to system properties and further demonstrate how these metrics relate to performance of some GSP techniques. We also discuss the feasibility of a data-driven approach that improves these metrics and apply it to a water distribution scenario. Overall, we find that many of the candidate systems analyzed are properly structured in the chosen GFT basis and amenable to GSP techniques, but identify considerable variability and nuance that merits future investigation.
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