Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals

Myung Cho; Jian Feng Cai; Suhui Liu; Yonina C. Eldar; Weiyu Xu

doi:10.1109/ICASSP.2016.7472556

Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals

Myung Cho, Jian Feng Cai, Suhui Liu, Yonina C. Eldar, Weiyu Xu

School of Engineering (Behrend)

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

4 Scopus citations

Abstract

We propose fast algorithms that speed up or improve the performance of recovering spectrally sparse signals from un-derdetermined measurements. Our algorithms are based on a non-convex approach of using alternating projected gradient descent for structured matrix recovery. We apply this approach to two formulations of structured matrix recovery: Hankel and Toeplitz mosaic structured matrix, and Hankel structured matrix. Our methods provide better recovery performance, and faster signal recovery than existing algorithms, including atomic norm minimization.

Original language	English (US)
Title of host publication	2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4638-4642
Number of pages	5
ISBN (Electronic)	9781479999880
DOIs	https://doi.org/10.1109/ICASSP.2016.7472556
State	Published - May 18 2016
Event	41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China Duration: Mar 20 2016 → Mar 25 2016

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2016-May
ISSN (Print)	1520-6149

Conference

Conference	41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
Country	China
City	Shanghai
Period	3/20/16 → 3/25/16

Fingerprint

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Electrical and Electronic Engineering

Cite this

Cho, M., Cai, J. F., Liu, S., Eldar, Y. C., & Xu, W. (2016). Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings (pp. 4638-4642). [7472556] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2016-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2016.7472556

Cho, Myung ; Cai, Jian Feng ; Liu, Suhui ; Eldar, Yonina C. ; Xu, Weiyu. / Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 4638-4642 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

@inproceedings{5679e4dc29bf46edba5820eafe82f24f,

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abstract = "We propose fast algorithms that speed up or improve the performance of recovering spectrally sparse signals from un-derdetermined measurements. Our algorithms are based on a non-convex approach of using alternating projected gradient descent for structured matrix recovery. We apply this approach to two formulations of structured matrix recovery: Hankel and Toeplitz mosaic structured matrix, and Hankel structured matrix. Our methods provide better recovery performance, and faster signal recovery than existing algorithms, including atomic norm minimization.",

author = "Myung Cho and Cai, {Jian Feng} and Suhui Liu and Eldar, {Yonina C.} and Weiyu Xu",

year = "2016",

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booktitle = "2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings",

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note = "41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 ; Conference date: 20-03-2016 Through 25-03-2016",

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Cho, M, Cai, JF, Liu, S, Eldar, YC & Xu, W 2016, Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals. in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings., 7472556, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2016-May, Institute of Electrical and Electronics Engineers Inc., pp. 4638-4642, 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, Shanghai, China, 3/20/16. https://doi.org/10.1109/ICASSP.2016.7472556

Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals. / Cho, Myung; Cai, Jian Feng; Liu, Suhui; Eldar, Yonina C.; Xu, Weiyu.

2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 4638-4642 7472556 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2016-May).

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

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Cho M, Cai JF, Liu S, Eldar YC, Xu W. Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 4638-4642. 7472556. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2016.7472556

Access to Document

10.1109/ICASSP.2016.7472556