Abstract
This letter demonstrates that sparse recovery can be achieved by an ℓ1-minimization ersatz easily implemented using a conventional nonnegative least squares algorithm. A connection with orthogonal matching pursuit is also highlighted. The preliminary results call for more investigations on the potential of the method and on its relations to classical sparse recovery algorithms.
Original language | English (US) |
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Article number | 6750023 |
Pages (from-to) | 498-502 |
Number of pages | 5 |
Journal | IEEE Signal Processing Letters |
Volume | 21 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2014 |
All Science Journal Classification (ASJC) codes
- Signal Processing
- Electrical and Electronic Engineering
- Applied Mathematics