Restricted Isometry Constants Where $\ell ^{p}$ Sparse Recovery Can Fail for $0≪ p \leq 1$
IEEE Transactions on Information Theory(2009)
摘要
This paper investigates conditions under which the solution of an underdetermined linear system with minimal lscrp norm, 0 < p les 1, is guaranteed to be also the sparsest one. Matrices are constructed with restricted isometry constants (RIC) delta2m arbitrarily close to 1/radic2 ap 0.707 where sparse recovery with p = 1 fails for at least one m-sparse vector, as well as matrices with delta2m arbi...
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关键词
Sparse matrices,Dictionaries,Minimization methods,Inverse problems,Linear systems,Signal processing,Delay,Iterative algorithms,Signal representations,Vectors
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