Computing and analyzing recoverable supports for sparse reconstruction

@article{Kruschel2015ComputingAA,
  title={Computing and analyzing recoverable supports for sparse reconstruction},
  author={Christian Kruschel and Dirk A. Lorenz},
  journal={Advances in Computational Mathematics},
  year={2015},
  volume={41},
  pages={1119-1144}
}
Designing computational experiments involving ℓ1 minimization with linear constraints in a finite-dimensional, real-valued space for receiving a sparse solution with a precise number k of nonzero entries is, in general, difficult. Several conditions were introduced which guarantee that, for example for small k or for certain matrices, simply placing entries with desired characteristics on a randomly chosen support will produce vectors which can be recovered by ℓ1 minimization. In this work, we… 
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