Journal of Mathematical Sciences: Advances and Applications
Author's: Fengong Wu, Donghui Li and Junfei Cao
Pages: [21] - [39]
Received Date: February 24, 2017
Submitted by:
DOI: http://dx.doi.org/10.18642/jmsaa_7100121782
We are concerned with the recovery of both sparse and partially sparse
signals via 
minimization. In sparse recovery, the
concept of null space property via 
(p-NSP) and the concept of
p-restricted isometry property (p-RIP) for 
are very important, while the relation
between them has not been studied. First, we will investigate the
relation between the p-RIP and the p-NSP. Using the
p-RIP, we get a sufficient condition for sparse signal recovery
from noisy measurements. Then, we generalize these properties to the
partially sparse recovery and extend the result to partially sparse
recovery based on the partially p-RIP.
compressed sensing, sparse signal recovery, partially sparse recovery,
minimization, restricted isometry property.
