Sparse recovery for compressive sensing via weighted Lp−q model
نویسندگان
چکیده
In this paper, we study weighted Lp?q minimization model which comprises non-smooth, nonconvex and non-Lipschitz quasi-norm Lp(0 < p ? 1) Lq(1 q 2) for recovering sparse signals. Based on the restricted isometry property (RIP) condition, obtain exact signal recovery result. We also theoretical bound when measurements are depraved by noises.
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ژورنال
عنوان ژورنال: Filomat
سال: 2022
ISSN: ['2406-0933', '0354-5180']
DOI: https://doi.org/10.2298/fil2214709n