Sparsity and incoherence in compressive sampling. (English) Zbl 1120.94005

Candès, Emmanuel; Romberg, Justin

Inverse Probl. 23, No. 3, 969-985 (2007).

The paper deals with the problem of reconstructing a sparse signal from a limited number of linear measurements. It is shown that if the number of randomly selected samples is sufficiently large (as defined by a mathematical expression involving the number of nonzero components in the signals and the largest entry in the observation matrix) then it will be possible to recover the signal by using a \(L_{1}\) norm minimization technique

Reviewer: Guy Jumarie (Montréal)

MSC:

94A12	Signal theory (characterization, reconstruction, filtering, etc.)
94A05	Communication theory

Keywords:

Signal reconstruction; sparse signal; compressing sampling; partial measurement