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Compressive Sensing over Graphs
[article]
2010
arXiv
pre-print
In this paper, motivated by network inference and tomography applications, we study the problem of compressive sensing for sparse signal vectors over graphs. In particular, we are interested in recovering sparse vectors representing the properties of the edges from a graph. Unlike existing compressive sensing results, the collective additive measurements we are allowed to take must follow connected paths over the underlying graph. For a sufficiently connected graph with n nodes, it is shown
arXiv:1008.0919v1
fatcat:ilz4ognowzb7neabiduqwzox3a