Large scale 2D spectral compressed sensing in continuous domain

Jian-Feng Cai, Weiyu Xu, Yang Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


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.
Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages5
ISBN (Print)9781509041176
StatePublished - Jun 20 2017
Externally publishedYes

Bibliographical note

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.


Dive into the research topics of 'Large scale 2D spectral compressed sensing in continuous domain'. Together they form a unique fingerprint.

Cite this