Revisiting compressed sensing: exploiting the efficiency of simplex and sparsification methods

We propose two approaches to solve large-scale compressed sensing problems. The first approach uses the parametric simplex method to recover very sparse signals by taking a small number of simplex pivots, while the second approach reformulates the problem using Kronecker products to achieve faster c...

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Bibliographic Details
Main Authors: Vanderbei, Robert (Author), Lin, Kevin (Author), Liu, Han (Author), Wang, Lie (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Mathematics (Contributor)
Format: Article
Language:English
Published: Springer Berlin Heidelberg, 2017-03-17T22:54:33Z.
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