Computer Science – Information Theory
Scientific paper
2010-05-18
Computer Science
Information Theory
10 pages
Scientific paper
In this note, we investigate the theoretical properties of Orthogonal Matching Pursuit (OMP), a class of decoder to recover sparse signal in compressed sensing. In particular, we show that the OMP decoder can give $(p,q)$ instance optimality for a large class of encoders with $1\leq p\leq q \leq 2$ and $(p,q)\neq (2,2)$. We also show that, if the encoding matrix is drawn from an appropriate distribution, then the OMP decoder is $(2,2)$ instance optimal in probability.
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