The Generalized Likelihood Ratio Test and the Sparse Representations Approach

@inproceedings{Fuchs2009TheGL,
  title={The Generalized Likelihood Ratio Test and the Sparse Representations Approach},
  author={Jean-Jacques Fuchs},
  booktitle={ICISP},
  year={2009}
}
When sparse representation techniques are used to tentatively recover the true sparse underlying model hidden in an observation vector, they can be seen as solving a joint detection and estimation problem. We consider the l2 - 11 regularized criterion, that is probably the most used in the sparse representation community, and show that, from a detection point of view, minimizing this criterion is similar to applying the Generalized Likelihood Ratio Test. More specifically tuning the… CONTINUE READING

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