1 Minimization with Noisy Data
نویسنده
چکیده
Compressed sensing aims at recovering a sparse signal x ∈ RN from few nonadaptive, linear measurements Φ(x) given by a measurement matrix Φ. One of the fundamental recovery algorithms is an `1 minimisation. In this paper we investigate the situation when our measurement Φ(x) is contaminated by arbitrary noise under the assumption that the matrix Φ satisfies the restricted isometry property. This complements results from [4] and [8].
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عنوان ژورنال:
- SIAM J. Numerical Analysis
دوره 50 شماره
صفحات -
تاریخ انتشار 2012