TY - JOUR T1 - Support Recovery from Noisy Measurement via Orthogonal Multi-Matching Pursuit JO - Numerical Mathematics: Theory, Methods and Applications VL - 2 SP - 185 EP - 192 PY - 2016 DA - 2016/09 SN - 9 DO - http://doi.org/10.4208/nmtma.2016.m1424 UR - https://global-sci.org/intro/article_detail/nmtma/12373.html KW - AB -

In this paper, a new stopping rule is proposed for orthogonal multi-matching pursuit (OMMP). We show that, for $ℓ_2$ bounded noise case, OMMP with the new stopping rule can recover the true support of any $K$-sparse signal $x$ from noisy measurements $y = Φx + e$ in at most $K$ iterations, provided that all the nonzero components of $x$ and the elements of the matrix $Φ$ satisfy certain requirements. The proposed method can improve the existing result. In particular, for the noiseless case, OMMP can exactly recover any $K$-sparse signal under the same RIP condition.