5 accepted papers
In recent years the convergence behavior of random node asynchronous graph communications have been studied for the case of undirected graphs. This paper extends these results to the case of graphs having arbitrary directed edges possibly with a non-diagonalizable adjacency matrix. Assuming that the…
This paper considers a node-asynchronous implementation of rational ("IIR") filters on graphs, in which the nodes are assumed to wake up randomly and independently from each other, and communicate only with their immediate neighbors. The underlying graph is allowed to be directed, possibly with a no…
This paper considers an autonomous network in which the nodes communicate only with their neighbors at random time instances, repeatedly and independently. Polynomial graph filters studied in the context of graph signal processing are inadequate to analyze signals on this type of networks. This is d…
In order to analyze signals defined over graphs, many concepts from the classical signal processing theory have been extended to the graph case. One of these concepts is the uncertainty principle, which studies the concentration of a signal on a graph and its graph Fourier basis (GFB). An eigenvecto…
Signal processing on graphs finds applications in many areas. Motivated by recent developments, this paper studies the concept of spectrum folding (aliasing) for graph signals under the downsample-then-upsample operation. In this development, we use a special eigenvector structure that is unique to…