pith. sign in

arxiv: 1005.0267 · v1 · submitted 2010-05-03 · 💻 cs.IT · math.IT

Recovery of sparsest signals via ell^q-minimization

classification 💻 cs.IT math.IT
keywords mathbbvectormeasurementminimizationsparsedeterminedeveryexactly
0
0 comments X
read the original abstract

In this paper, it is proved that every $s$-sparse vector ${\bf x}\in {\mathbb R}^n$ can be exactly recovered from the measurement vector ${\bf z}={\bf A} {\bf x}\in {\mathbb R}^m$ via some $\ell^q$-minimization with $0< q\le 1$, as soon as each $s$-sparse vector ${\bf x}\in {\mathbb R}^n$ is uniquely determined by the measurement ${\bf z}$.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.