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...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Berlin Heidelberg
2017
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| Online Access: | http://hdl.handle.net/1721.1/107484 https://orcid.org/0000-0003-3582-8898 |