论文标题
时间序列在网络物理系统中检测的子空间方法
A Subspace Method for Time Series Anomaly Detection in Cyber-Physical Systems
论文作者
论文摘要
时间序列异常检测是系统监测和模型切换的重要过程，以及网络物理系统中的其他应用。在本文档中，我们为时间序列异常检测提出了一种快速的子空间方法，其计算成本相对较低，该方法已设计用于与动态系统相对应的真实传感器信号中的异常检测。我们还提出了一些与我们方法的理论基础相对应的一般结果，以及用于时间序列异常检测的典型算法。提出了一些与原型算法应用相对应的数值示例，并提供了一些基于本文中介绍的理论和算法的计算工具。
Time series anomaly detection is an important process for system monitoring and model switching, among other applications in cyber-physical systems. In this document, we present a fast subspace method for time series anomaly detection, with a relatively low computational cost, that has been designed for anomaly detection in real sensor signals corresponding to dynamical systems. We also present some general results corresponding to the theoretical foundations of our method, together with a prototypical algorithm to for time series anomaly detection. Some numerical examples corresponding to applications of the prototypical algorithm are presented, and some computational tools based on the theory and algorithms presented in this paper, are provided.
