Piecewise sparse signal recovery via piecewise orthogonal matching pursuit
Kezhi Li, Cristian R. Rojas, Tao Yang, Håkan Hjalmarsson, Karl Henrik Johansson, Shuang Cong
Abstract
In this paper, we consider the recovery of piecewise sparse signals from incomplete noisy measurements via a greedy algorithm. Here piecewise sparse means that the signal can be approximated in certain domain with known number of nonzero entries in each piece/segment. This paper makes a two-fold contribution to this problem: 1) formulating a piecewise sparse model in the framework of compressed sensing and providing the theoretical analysis of corresponding sensing matrices; 2) developing a greedy algorithm called piecewise orthogonal matching pursuit (POMP) for the recovery of piecewise sparse signals. Experimental simulations verify the effectiveness of the proposed algorithms.
BibTeX
@inproceedings{icassp2016_piecewisesparses,
title = {Piecewise sparse signal recovery via piecewise orthogonal matching pursuit},
author = {Kezhi Li and Cristian R. Rojas and Tao Yang and Håkan Hjalmarsson and Karl Henrik Johansson and Shuang Cong},
booktitle = {ICASSP 2016},
year = {2016}
}