Robustness of orthogonal matching pursuit for multiple measurement vectors in noisy scenario

Jie Ding; Laming Chen; Yuantao Gu

doi:10.1109/ICASSP.2012.6288748

Robustness of orthogonal matching pursuit for multiple measurement vectors in noisy scenario

Jie Ding, Laming Chen, Yuantao Gu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Scopus citations

Abstract

In this paper, we consider orthogonal matching pursuit (OMP) algorithm for multiple measurement vectors (MMV) problem. The robustness of OMPMMV is studied under general perturbations-when the measurement vectors as well as the sensing matrix are incorporated with additive noise. The main result shows that although exact recovery of the sparse solutions is unrealistic in noisy scenario, recovery of the support set of the solutions is guaranteed under suitable conditions. Specifically, a sufficient condition is derived that guarantees exact recovery of the sparse solutions in noiseless scenario.

Original language	English (US)
Title of host publication	2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages	3813-3816
Number of pages	4
DOIs	https://doi.org/10.1109/ICASSP.2012.6288748
State	Published - Oct 23 2012
Externally published	Yes
Event	2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan Duration: Mar 25 2012 → Mar 30 2012

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)	1520-6149

Other

Other	2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
Country/Territory	Japan
City	Kyoto
Period	3/25/12 → 3/30/12

Keywords

Multiple measurement vectors (MMV)
compressive sensing (CS)
general perturbations
orthogonal matching pursuit (OMP)

Publisher link

10.1109/ICASSP.2012.6288748

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Ding, J., Chen, L., & Gu, Y. (2012). Robustness of orthogonal matching pursuit for multiple measurement vectors in noisy scenario. In 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings (pp. 3813-3816). Article 6288748 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2012.6288748

Robustness of orthogonal matching pursuit for multiple measurement vectors in noisy scenario. / Ding, Jie; Chen, Laming; Gu, Yuantao.
2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings. 2012. p. 3813-3816 6288748 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ding, J, Chen, L & Gu, Y 2012, Robustness of orthogonal matching pursuit for multiple measurement vectors in noisy scenario. in 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings., 6288748, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 3813-3816, 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012, Kyoto, Japan, 3/25/12. https://doi.org/10.1109/ICASSP.2012.6288748

Ding J, Chen L, Gu Y. Robustness of orthogonal matching pursuit for multiple measurement vectors in noisy scenario. In 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings. 2012. p. 3813-3816. 6288748. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.2012.6288748

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Robustness of orthogonal matching pursuit for multiple measurement vectors in noisy scenario

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