Sparse recovery with pre-Gaussian random matrices Academic Article

abstract

• 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 > cs In (e N/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. Instytut Matematyczny PAN, 2010.

authors

• Foucart, Simon

published proceedings

• STUDIA MATHEMATICA

author list (cited authors)

• Foucart, S., & Lai, M.

citation count

• 20

complete list of authors

• Foucart, Simon||Lai, Ming-Jun

publication date

• December 2010

publisher

• Institute of Mathematics, Polish Academy of Sciences  Publisher

published in

• Studia Mathematica  Journal

keywords

• Compressed Sensing
• L(1)-minimization
• Pre-gaussian Random Variables
• Random Matrices
• Sparse Recovery

Digital Object Identifier (DOI)

• 10.4064/sm200-1-6

start page

• 91

end page

• 102

volume

• 200

issue

• 1

URL

• http://dx.doi.org/10.4064/sm200-1-6