论文标题
本地网络可识别性，并进行部分激发和测量
Local Network Identifiability with Partial Excitation and Measurement
论文作者
论文摘要
这项工作着重于具有部分激发和测量的动力网络的可识别性：根据已知拓扑结构，一组节点通过未知传输函数互连，某些节点会受到外部激发的约束，并且测量了一些节点。目的是根据从激发和测量节点收集的输入输出数据来确定网络中的哪些传输函数。 我们提出了一个本地版本的网络可识别性，代表了恢复近似已知的传输功能的能力，或者将其恢复到离散的歧义。我们表明，局部可识别性是一种通用属性，在矩阵通用等级方面建立了必要且充分的条件，并利用此条件来开发确定算法的确定，并使用概率1，传输功能在本地可识别。我们的实施以图形方式介绍了结果，并可以公开使用。
This work focuses on the identifiability of dynamical networks with partial excitation and measurement: a set of nodes are interconnected by unknown transfer functions according to a known topology, some nodes are subject to external excitation, and some nodes are measured. The goal is to determine which transfer functions in the network can be recovered based on the input-output data collected from the excited and measured nodes. We propose a local version of network identifiability, representing the ability to recover transfer functions which are approximately known, or to recover them up to a discrete ambiguity. We show that local identifiability is a generic property, establish a necessary and sufficient condition in terms of matrix generic ranks, and exploit this condition to develop an algorithm determining, with probability 1, which transfer functions are locally identifiable. Our implementation presents the results graphically, and is publicly available.
