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Estimating sparse signals using integrated wide-band dictionaries

Butsenko, Maksim; Sward, Johan LU and Jakobsson, Andreas LU (2017) 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings p.4426-4430
Abstract

In this paper, we present a technique for reducing the size of the dictionary in sparse signal reconstruction by formulating an initial dictionary containing elements that spans bands of the considered parameter space. We allow for the use of this banded dictionary in a first-stage estimation procedure, in which large parts of the parameter space is discarded for further analysis, thereby reducing the overall computationally complexity required to allow for a reliable signal reconstruction. We illustrate the presented principle on the problem of estimating sinusoidal components corrupted by white noise.

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
convex optimization, dictionary learning, Sparse signal reconstruction
in
2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
pages
5 pages
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
external identifiers
  • scopus:85023748591
ISBN
9781509041176
DOI
10.1109/ICASSP.2017.7952993
language
English
LU publication?
yes
id
2335ac96-9500-4638-ab8b-f376109f6654
date added to LUP
2017-07-27 14:07:47
date last changed
2018-01-07 12:13:26
@inproceedings{2335ac96-9500-4638-ab8b-f376109f6654,
  abstract     = {<p>In this paper, we present a technique for reducing the size of the dictionary in sparse signal reconstruction by formulating an initial dictionary containing elements that spans bands of the considered parameter space. We allow for the use of this banded dictionary in a first-stage estimation procedure, in which large parts of the parameter space is discarded for further analysis, thereby reducing the overall computationally complexity required to allow for a reliable signal reconstruction. We illustrate the presented principle on the problem of estimating sinusoidal components corrupted by white noise.</p>},
  author       = {Butsenko, Maksim and Sward, Johan and Jakobsson, Andreas},
  booktitle    = {2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings},
  isbn         = {9781509041176},
  keyword      = {convex optimization,dictionary learning,Sparse signal reconstruction},
  language     = {eng},
  month        = {06},
  pages        = {4426--4430},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Estimating sparse signals using integrated wide-band dictionaries},
  url          = {http://dx.doi.org/10.1109/ICASSP.2017.7952993},
  year         = {2017},
}