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Methods for Distributed Compressed SensingDOI: 10.3390/jsan3010001 Keywords: distributed compressed sensing, distributed greedy pursuit, greedy algorithms Abstract: Compressed sensing is a thriving research field covering a class of problems where a large sparse signal is reconstructed from a few random measurements. In the presence of several sensor nodes measuring correlated sparse signals, improvements in terms of recovery quality or the requirement for a fewer number of local measurements can be expected if the nodes cooperate. In this paper, we provide an overview of the current literature regarding distributed compressed sensing; in particular, we discuss aspects of network topologies, signal models and recovery algorithms.
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