Sparse recovery with pre-Gaussian random matrices - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Studia Mathematica Year : 2010

Sparse recovery with pre-Gaussian random matrices


For an m×N underdetermined system of linear equations with independent pre-Gaussian random coefficients satisfying simple moment conditions, it is proved that the s-sparse solutions of the system can be found by ℓ1-minimization under the optimal condition m≥csln(eN/s). The main ingredient of the proof is a variation of a classical Restricted Isometry Property, where the inner norm becomes the ℓ1-norm and the outer norm depends on probability distributions.

Dates and versions

hal-00767062 , version 1 (19-12-2012)



Simon Foucart, Ming-Jun Lai. Sparse recovery with pre-Gaussian random matrices. Studia Mathematica, 2010, 200, pp.91--102. ⟨10.4064/sm200-1-6⟩. ⟨hal-00767062⟩
45 View
0 Download



Gmail Facebook Twitter LinkedIn More