DIstributed Change Point Detection in Streaming Manifold-Valued Signals Over Graphs
- Resource Type
- Conference
- Authors
- Wang, Xiuheng; Borsoi, Ricardo Augusto; Richard, Cedric; Ferrari, Andre
- Source
- 2023 57th Asilomar Conference on Signals, Systems, and Computers Signals, Systems, and Computers, 2023 57th Asilomar Conference on. :689-693 Oct, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Manifolds
Geometry
Network topology
Simulation
Time series analysis
Signal processing algorithms
Signal processing
Graph signal processing
distributed
change point detection
Riemannian manifold
graph filtering
- Language
- ISSN
- 2576-2303
Signal processing methods over graphs and networks have recently been proposed to detect change points occurring in lo-calized communities of nodes. Nevertheless, all these methods are mostly limited to time series data in Euclidean spaces. In this paper, we devise a distributed change point detection method for streaming manifold-valued signals over graphs. This framework combines a local test statistic at each node to account for the geometry of the data residing on a Riemannian manifold, with a fully distributed graph filter that incor-porates information on network topology. This significantly improves the detection of change points in unknown communities of networks.