Abstract:
In this paper, we present a concise analysis of the constrained lq(0 < q = 1)- minimization method for sparse signal recovery. The obtained results are helpful in underst...Show MoreMetadata
Abstract:
In this paper, we present a concise analysis of the constrained lq(0 < q = 1)- minimization method for sparse signal recovery. The obtained results are helpful in understanding the recovery capability of lq-minimization, and meaningful in the development of compressed sensing technology.
Date of Conference: 14-15 May 2011
Date Added to IEEE Xplore: 18 July 2011
Electronic ISBN:978-1-61284-314-8
Contents 