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The new model may have a sparse solution.
Then (hat{x}) can be regarded as a sparse solution of the (operatorname{LCP} q,M)).
Then x ¯ can be regard as a sparse solution of the LCP ( q, M ).
However, the signal recovery is reduced to seeking a sparse solution to an underdetermined linear system of equations.
Comparing MKL with Lp-norm(p≥2), SMKL obtains a sparse solution by a pre-selection procedure.
Hence, the algorithm with the generalized shrinkage operator converges to a sparse solution and is robust to noises.
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With this simple Example 1, we should be aware that the MMV problem wants a jointly sparse solution, not a solution which is just composed of sparse vectors.
Thus, if a less sparse solution yields a higher generalization performance (as estimated by cross-validation) than a more sparse solution, then the less sparse solution is selected.
If the matrix A satisfies a rank condition, this problem has a unique, sparse solution.
The test is associated with the Z-matrix which has an important property, that is, there is a unique sparse solution of LCPs when M is a kind of Z-matrix [5].
Also, the 2D IAA which is a nonparametric algorithm is presented in [29] for a general sparse solution.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com