Recovering sparse signals with non-convex penalties and DC programming

@inproceedings{Gasso2008RecoveringSS,
  title={Recovering sparse signals with non-convex penalties and DC programming},
  author={Gilles Gasso and Alain Rakotomamonjy and St{\'e}phane Canu Litis},
  year={2008}
}
This paper considers the problem of recovering a sparse sign al representation according to a signal dictionary. This problem is usually formalized as a penaliz ed least-squares problem in which sparsity is usually induced by al1-norm penalty on the coefficient. Such an approach known as th e Lassoor Basis Pursuit Denoisinghas been shown to perform reasonably well in some situations . However, it has also been proved that non-convex penalties like lq-norm with q < 1 or SCAD penalty are able to… CONTINUE READING
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