English

Recovery of sparsest signals via $\ell^q$-minimization

Information Theory 2010-05-04 v1 math.IT

Abstract

In this paper, it is proved that every ss-sparse vector xRn{\bf x}\in {\mathbb R}^n can be exactly recovered from the measurement vector z=AxRm{\bf z}={\bf A} {\bf x}\in {\mathbb R}^m via some q\ell^q-minimization with 0<q10< q\le 1, as soon as each ss-sparse vector xRn{\bf x}\in {\mathbb R}^n is uniquely determined by the measurement z{\bf z}.

Keywords

Cite

@article{arxiv.1005.0267,
  title  = {Recovery of sparsest signals via $\ell^q$-minimization},
  author = {Qiyu Sun},
  journal= {arXiv preprint arXiv:1005.0267},
  year   = {2010}
}