A Sufficient Condition for Restoring Sparse Vectors from
$\ell_1-\ell_2$-minimization with
Cumulative Coherence
Abstract
This paper focuses on the compressed sensing
$\ell_1-\ell_2-$minimization model and
develops new bounds on cumulative coherence
$\mu_1(s)$. We point out that if cumulative coherence
$\mu_1(s)$ satisfies (2) or (11), then the sparse
signal can stably recover in noise model and exactly recover in free
noise by $\ell_1-\ell_2$-minimization
model.
