Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Digital processing of random signals: theory and methods
Digital processing of random signals: theory and methods
On the application of the global matched filter to DOA estimation with uniform circular arrays
IEEE Transactions on Signal Processing
On sparse representations in arbitrary redundant bases
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
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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 regularization parameter in the criterion amounts to set the threshold in the Generalized Likelihood Ratio Test.