Phaseless super-resolution in the continuous domain

Myung Cho; Christos Thrampoulidis; Weiyu Xu; Babak Hassibi

doi:10.1109/ICASSP.2017.7952870

Phaseless super-resolution in the continuous domain

Myung Cho, Christos Thrampoulidis, Weiyu Xu, Babak Hassibi

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

2 Scopus citations

Abstract

Phaseless super-resolution refers to the problem of super-resolving a signal from only its low-frequency Fourier magnitude measurements. In this paper, we consider the phaseless super-resolution problem of recovering a sum of sparse Dirac delta functions which can be located anywhere in the continuous time-domain. For such signals in the continuous domain, we propose a novel Semidefinite Programming (SDP) based signal recovery method to achieve the phaseless super-resolution. This work extends the recent work of Jaganathan et al. [1], which considered phaseless super-resolution for discrete signals on the grid.

Original language	English (US)
Title of host publication	2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher	IEEE
Pages	3814-3818
Number of pages	5
ISBN (Print)	9781509041176
DOIs	https://doi.org/10.1109/ICASSP.2017.7952870
State	Published - Jun 19 2017
Externally published	Yes

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10.1109/ICASSP.2017.7952870

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title = "Phaseless super-resolution in the continuous domain",

abstract = "Phaseless super-resolution refers to the problem of super-resolving a signal from only its low-frequency Fourier magnitude measurements. In this paper, we consider the phaseless super-resolution problem of recovering a sum of sparse Dirac delta functions which can be located anywhere in the continuous time-domain. For such signals in the continuous domain, we propose a novel Semidefinite Programming (SDP) based signal recovery method to achieve the phaseless super-resolution. This work extends the recent work of Jaganathan et al. [1], which considered phaseless super-resolution for discrete signals on the grid.",

author = "Myung Cho and Christos Thrampoulidis and Weiyu Xu and Babak Hassibi",

note = "KAUST Repository Item: Exported on 2022-06-28 Acknowledged KAUST grant number(s): OCRF-2014-CRG-3 Acknowledgements: The work of Weiyu Xu is supported by Simons Foundation 318608, KAUST OCRF-2014-CRG-3, NSF DMS-1418737 and NIH 1R01EB020665-01. This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

year = "2017",

month = jun,

day = "19",

doi = "10.1109/ICASSP.2017.7952870",

language = "English (US)",

isbn = "9781509041176",

pages = "3814--3818",

booktitle = "2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",

publisher = "IEEE",

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TY - GEN

T1 - Phaseless super-resolution in the continuous domain

AU - Cho, Myung

AU - Thrampoulidis, Christos

AU - Xu, Weiyu

AU - Hassibi, Babak

N1 - KAUST Repository Item: Exported on 2022-06-28 Acknowledged KAUST grant number(s): OCRF-2014-CRG-3 Acknowledgements: The work of Weiyu Xu is supported by Simons Foundation 318608, KAUST OCRF-2014-CRG-3, NSF DMS-1418737 and NIH 1R01EB020665-01. This publication acknowledges KAUST support, but has no KAUST affiliated authors.

PY - 2017/6/19

Y1 - 2017/6/19

N2 - Phaseless super-resolution refers to the problem of super-resolving a signal from only its low-frequency Fourier magnitude measurements. In this paper, we consider the phaseless super-resolution problem of recovering a sum of sparse Dirac delta functions which can be located anywhere in the continuous time-domain. For such signals in the continuous domain, we propose a novel Semidefinite Programming (SDP) based signal recovery method to achieve the phaseless super-resolution. This work extends the recent work of Jaganathan et al. [1], which considered phaseless super-resolution for discrete signals on the grid.

AB - Phaseless super-resolution refers to the problem of super-resolving a signal from only its low-frequency Fourier magnitude measurements. In this paper, we consider the phaseless super-resolution problem of recovering a sum of sparse Dirac delta functions which can be located anywhere in the continuous time-domain. For such signals in the continuous domain, we propose a novel Semidefinite Programming (SDP) based signal recovery method to achieve the phaseless super-resolution. This work extends the recent work of Jaganathan et al. [1], which considered phaseless super-resolution for discrete signals on the grid.

UR - http://hdl.handle.net/10754/679386

UR - http://ieeexplore.ieee.org/document/7952870/

UR - http://www.scopus.com/inward/record.url?scp=85023772955&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2017.7952870

DO - 10.1109/ICASSP.2017.7952870

M3 - Conference contribution

SN - 9781509041176

SP - 3814

EP - 3818

BT - 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

PB - IEEE

ER -

Phaseless super-resolution in the continuous domain

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