@inproceedings{5679e4dc29bf46edba5820eafe82f24f,
title = "Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals",
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",
month = may,
day = "18",
doi = "10.1109/ICASSP.2016.7472556",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4638--4642",
booktitle = "2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings",
address = "United States",
note = "41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 ; Conference date: 20-03-2016 Through 25-03-2016",
}