Titlebook: Compressed Sensing for Distributed Systems; Giulio Coluccia,Chiara Ravazzi,Enrico Magli Book 2015 The Author(s) 2015 Compressed Sensing.Di

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Distributed Recovery,r nodes that collect measurements from different sensors. This estimation problem can be recast into an optimization problem where a convex and separable loss function should be minimized subject to sparsity constraints. The goal of the network is to handle distributed sparse estimation. Clearly, to

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SpringerBriefs in Electrical and Computer Engineeringhttp://image.papertrans.cn/c/image/231980.jpg

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https://doi.org/10.1007/978-3-8350-9173-3This chapter motivates the problem of distributed compressed sensing. It recalls the basic properties of compressed sensing and describes why it can be an appealing technique for distributed systems. It highlights existing and possible future applications in this area.

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Introduction,This chapter motivates the problem of distributed compressed sensing. It recalls the basic properties of compressed sensing and describes why it can be an appealing technique for distributed systems. It highlights existing and possible future applications in this area.

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