Control of Graph Signals Over Random Time-Varying Graphs

In this work, we jointly exploit tools from graph signal processing and control theory to drive a bandlimited graph signal that is being diffused on a random time-varying graph from a subset of nodes. As our main contribution, we rely only on the statistics of the graph to introduce the concept of controllability in the mean, and therefore drive the signal on the expected graph to a desired bandlimited state. A mean-square error (MSE) analysis is performed for two main tasks: i) to highlight the role played by the signal bandwidth and the control nodes to the deviation from the mean signal of a particular realization; and ii) to select the control nodes and design the control signal that minimize this MSE. Numerical results validate the introduced controllability in the mean framework and show its ability to cope with time-varying topologies.