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ICASSP
2011
IEEE
13 years 5 days ago
Deterministic compressed-sensing matrices: Where Toeplitz meets Golay
Recently, the statistical restricted isometry property (STRIP) has been formulated to analyze the performance of deterministic sampling matrices for compressed sensing. In this pa...
Kezhi Li, Cong Ling, Lu Gan
CORR
2007
Springer
110views Education» more  CORR 2007»
13 years 8 months ago
Free deconvolution for signal processing applications
—Situations in many fields of research, such as digital communications, nuclear physics and mathematical finance, can be modelled with random matrices. When the matrices get la...
Øyvind Ryan, Mérouane Debbah
CORR
2010
Springer
133views Education» more  CORR 2010»
13 years 8 months ago
Nonuniform Sparse Recovery with Gaussian Matrices
Compressive sensing predicts that sufficiently sparse vectors can be recovered from highly incomplete information. Efficient recovery methods such as 1-minimization find the sparse...
Ulas Ayaz, Holger Rauhut
CORR
2007
Springer
76views Education» more  CORR 2007»
13 years 8 months ago
Some problems in asymptotic convex geometry and random matrices motivated by numerical algorithms
Abstract. The simplex method in Linear Programming motivates several problems of asymptotic convex geometry. We discuss some conjectures and known results in two related directions...
Roman Vershynin
ISSAC
2007
Springer
131views Mathematics» more  ISSAC 2007»
14 years 2 months ago
Some recent progress in exact linear algebra and related questions
We describe some major recent progress in exact and symbolic linear algebra. These advances concern the improvement of complexity estimates for fundamental problems such as linear...
Gilles Villard