Paper ID | SPTM-16.2 | ||
Paper Title | NETWORK TOPOLOGY CHANGE-POINT DETECTION FROM GRAPH SIGNALS WITH PRIOR SPECTRAL SIGNATURES | ||
Authors | Chiraag Kaushik, T. Mitchell Roddenberry, Santiago Segarra, Rice University, United States | ||
Session | SPTM-16: Graph Topology Inference | ||
Location | Gather.Town | ||
Session Time: | Thursday, 10 June, 14:00 - 14:45 | ||
Presentation Time: | Thursday, 10 June, 14:00 - 14:45 | ||
Presentation | Poster | ||
Topic | Signal Processing Theory and Methods: [SIPG] Signal and Information Processing over Graphs | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
Abstract | We consider the problem of sequential graph topology change-point detection from graph signals. We assume that signals on the nodes of the graph are regularized by the underlying graph structure via a graph filtering model, which we then leverage to distill the graph topology change-point detection problem to a subspace detection problem. We demonstrate how prior information on the spectral signature of the post-change graph can be incorporated to implicitly denoise the observed sequential data, thus leading to a natural CUSUM-based algorithm for change-point detection. Numerical experiments illustrate the performance of our proposed approach, particularly underscoring the benefits of (potentially noisy) prior information. |