Real versus complex null space properties for sparse vector recovery

DOI10.1016/j.crma.2010.07.024zbMath1196.15008OpenAlexW1966749434MaRDI QIDQ990237

Simon Foucart, Rémi Gribonval

Publication date: 6 September 2010

Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)

Full work available at URL: https://hal.inria.fr/inria-00539612/file/FoGr09.pdf

zbMATH Keywords

convex polygonssparse solutionsnull space propertyunderdetermined systems of linear equationsminimal \(\ell _{1}\)-norm

Mathematics Subject Classification ID

Linear equations (linear algebraic aspects) (15A06)

Related Items (5)

Exact recovery of sparse multiple measurement vectors by \(l_{2,p}\)-minimization ⋮ Flavors of Compressive Sensing ⋮ Perturbations of measurement matrices and dictionaries in compressed sensing ⋮ Sparse recovery with coherent tight frames via analysis Dantzig selector and analysis LASSO ⋮ The null space property for sparse recovery from multiple measurement vectors

Cites Work

• The null space property for sparse recovery from multiple measurement vectors
• Highly sparse representations from dictionaries are unique and independent of the sparseness measure
• On quasivector spaces of convex bodies and zonotopes
• The Circumference of a Convex Polygon
• Theoretical and Empirical Results for Recovery From Multiple Measurements
• Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ ¹ minimization

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