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Total Variation Minimization in Compressed Sensing
April 07, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Felix Krahmer, Christian Kruschel, Michael Sandbichler
arXiv ID
1704.02105
Category
cs.IT: Information Theory
Citations
46
Venue
arXiv.org
Last Checked
6 months ago
Abstract
This chapter gives an overview over recovery guarantees for total variation minimization in compressed sensing for different measurement scenarios. In addition to summarizing the results in the area, we illustrate why an approach that is common for synthesis sparse signals fails and different techniques are necessary. Lastly, we discuss a generalizations of recent results for Gaussian measurements to the subgaussian case.
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