Analysis of Orthogonal Matching Pursuit for Compressed Sensing in Practical Settings

Autor:	Masoumi, Hamed, Verhaegen, Michel, Myers, Nitin Jonathan
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Signal Processing
Druh dokumentu:	Working Paper
Popis:	Orthogonal matching pursuit (OMP) is a widely used greedy algorithm for sparse signal recovery in compressed sensing (CS). Prior work on OMP, however, has only provided reconstruction guarantees under the assumption that the columns of the CS matrix have equal norms, which is unrealistic in many practical CS applications due to hardware constraints. In this paper, we derive sparse recovery guarantees with OMP, when the CS matrix has unequal column norms. Finally, we show that CS matrices whose column norms are comparable achieve tight guarantees for the successful recovery of the support of a sparse signal and a low mean squared error in the estimate. Comment: 5 pages, 2 figures, submitted to the IEEE Statistical Signal Processing Workshop 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2302.04056 Zobrazit plný text záznamu View this record from Arxiv