Open AccessExact support recovery via orthogonal matching pursuit from noisy measurements
Author(s) -
Dan Wei,
Fu Yu
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2016.1893
Subject(s) - matching pursuit , bounded function , noise (video) , algorithm , zero (linguistics) , matrix (chemical analysis) , matching (statistics) , signal reconstruction , basis pursuit , computer science , signal (programming language) , mathematics , signal to noise ratio (imaging) , signal processing , artificial intelligence , compressed sensing , mathematical analysis , telecommunications , statistics , image (mathematics) , linguistics , philosophy , materials science , radar , composite material , programming language
The support recovery performance of orthogonal matching pursuit (OMP) for the l ∞ bounded noise is presented. It is shown that OMP can exactly recover the support of arbitrary K ‐sparse signal x from noisy measurements y = Φ x + e in K iterations, provided that the matrix Φ and the minimum magnitude of all the non‐zero elements of x satisfy certain requirements. The proposed result is an improvement over the existing ones.