TY - GEN
T1 - Large scale 2D spectral compressed sensing in continuous domain
AU - Cai, Jian-Feng
AU - Xu, Weiyu
AU - Yang, Yang
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OCRF-2014-CRG-3
Acknowledgements: JFC is supported in part by Grant 16300616 of Hong Kong Research Grants Council. Weiyu Xu is supported by the Simons Foundation 318608 , KAUST OCRF-2014-CRG-3, NSF DMS-1418737 and NIH lROlEB020665-01
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2017/6/20
Y1 - 2017/6/20
N2 - We consider the problem of spectral compressed sensing in continuous domain, which aims to recover a 2-dimensional spectrally sparse signal from partially observed time samples. The signal is assumed to be a superposition of s complex sinusoids. We propose a semidefinite program for the 2D signal recovery problem. Our model is able to handle large scale 2D signals of size 500 × 500, whereas traditional approaches only handle signals of size around 20 × 20.
AB - We consider the problem of spectral compressed sensing in continuous domain, which aims to recover a 2-dimensional spectrally sparse signal from partially observed time samples. The signal is assumed to be a superposition of s complex sinusoids. We propose a semidefinite program for the 2D signal recovery problem. Our model is able to handle large scale 2D signals of size 500 × 500, whereas traditional approaches only handle signals of size around 20 × 20.
UR - http://hdl.handle.net/10754/625802
UR - http://ieeexplore.ieee.org/document/7953289/
UR - http://www.scopus.com/inward/record.url?scp=85023759895&partnerID=8YFLogxK
U2 - 10.1109/icassp.2017.7953289
DO - 10.1109/icassp.2017.7953289
M3 - Conference contribution
SN - 9781509041176
SP - 5905
EP - 5909
BT - 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -