Signal processing on graphs: Estimating the structure of a graph

This paper presents a computationally tractable algorithm for estimating the graph structure of graph signals is presented. The algorithm is demonstrated on simulated and real network time series datasets, and the performance of the new method is compared to that of related methods for estimating graph structure. The adjacency matrices estimated using the new method are shown to be close to the true graph in the simulated data and consistent with prior physical knowledge in the real dataset.