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Grid-less estimation of saturated signals

Elvander, Filip LU ; Swärd, Johan LU and Jakobsson, Andreas LU (2017) 51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017) p.372-376
Abstract
This work proposes a frequency and amplitude estimator tailored for noise corrupted signals that have been clipped. Formulated as a sparse reconstruction problem, the proposed algorithm estimates the signal parameters by solving an atomic norm minimization problem. The estimator also exploits the waveform information provided by the clipped samples, incorporated in the form of linear constraints that have been augmented by slack variables as to provide robustness to noise. Numerical examples indicate that the algorithm offers preferable performance as compared to methods not exploiting the saturated samples.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
atomic norm, de-clipping, gridless reconstruction
host publication
2017 51st Asilomar Conference on Signals, Systems, and Computers
pages
5 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017)
conference location
Pacific Grove, United States
conference dates
2017-10-29 - 2017-11-01
external identifiers
  • scopus:85050969108
ISBN
978-1-5386-1823-3
DOI
10.1109/ACSSC.2017.8335204
language
English
LU publication?
yes
id
43044354-2e74-4f0a-9450-e95c56dc20f4
date added to LUP
2018-04-25 11:29:04
date last changed
2020-01-13 00:39:37
@inproceedings{43044354-2e74-4f0a-9450-e95c56dc20f4,
  abstract     = {This work proposes a frequency and amplitude estimator tailored for noise corrupted signals that have been clipped. Formulated as a sparse reconstruction problem, the proposed algorithm estimates the signal parameters by solving an atomic norm minimization problem. The estimator also exploits the waveform information provided by the clipped samples, incorporated in the form of linear constraints that have been augmented by slack variables as to provide robustness to noise. Numerical examples indicate that the algorithm offers preferable performance as compared to methods not exploiting the saturated samples.},
  author       = {Elvander, Filip and Swärd, Johan and Jakobsson, Andreas},
  booktitle    = {2017 51st Asilomar Conference on Signals, Systems, and Computers},
  isbn         = {978-1-5386-1823-3},
  language     = {eng},
  pages        = {372--376},
  publisher    = {IEEE - Institute of Electrical and Electronics Engineers Inc.},
  title        = {Grid-less estimation of saturated signals},
  url          = {http://dx.doi.org/10.1109/ACSSC.2017.8335204},
  doi          = {10.1109/ACSSC.2017.8335204},
  year         = {2017},
}