Observing Bandlimited Graph Processes from Subsampled Measurements

This work merges tools from graph signal processing and linear systems theory to propose sampling strategies for observing the initial state of a process evolving over a graph. The proposed method is ratified by a mathematical analysis that provides insights on the role played by the different actors, such as the graph topology, the process...

Distributed Wiener-Based Reconstruction of Graph Signals

This paper proposes strategies for distributed Wiener-based reconstruction of graph signals from subsampled measurements. Given a stationary signal on a graph, we fit a distributed autoregressive moving average graph filter to a Wiener graph frequency response and propose two reconstruction strategies: i) reconstruction from a single temporal...

Spectrum Sensing Using Energy Detectors with Performance Computation Capabilities

We focus on the performance of the energy detector for cognitive radio applications. Our aim is to incorporate, into the energy detector, low-complexity algorithms that compute the performance of the detector itself. The main parameters of interest are the probability of detection and the required number of samples. Since the exact performance...