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Smooth Time-Frequency Estimation using Covariance Fitting

Brynolfsson, Johan LU ; Swärd, Johan LU ; Jakobsson, Andreas LU and Sandsten, Maria LU (2014) 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP 2014) In Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on p.779-783
Abstract
In this paper, we introduce a time-frequency spectral estimator for smooth spectra, allowing for irregularly sampled measurements. A non-parametric representation of the time dependent (TD) covariance matrix is formed by assuming that the spectrum is piecewise linear. Using this representation, the time-frequency spectrum is then estimated by solving a convex covariance fitting problem, which also, as a byproduct, provides an enhanced estimation of the TD covariance matrix. Numerical examples using simulated non-stationary processes show the preferable performance of the proposed method as compared to the classical Wigner-Ville distribution and a smoothed spectrogram.
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Time-frequency analysis, convex optimization, smooth
in
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
pages
5 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP 2014)
external identifiers
  • wos:000343655300157
  • scopus:84905215259
ISSN
1520-6149
DOI
10.1109/ICASSP.2014.6853702
language
English
LU publication?
yes
id
9d959852-d49a-494b-b6b4-18d046c6916e (old id 4588285)
date added to LUP
2014-08-29 20:54:25
date last changed
2017-04-16 03:51:58
@inproceedings{9d959852-d49a-494b-b6b4-18d046c6916e,
  abstract     = {In this paper, we introduce a time-frequency spectral estimator for smooth spectra, allowing for irregularly sampled measurements. A non-parametric representation of the time dependent (TD) covariance matrix is formed by assuming that the spectrum is piecewise linear. Using this representation, the time-frequency spectrum is then estimated by solving a convex covariance fitting problem, which also, as a byproduct, provides an enhanced estimation of the TD covariance matrix. Numerical examples using simulated non-stationary processes show the preferable performance of the proposed method as compared to the classical Wigner-Ville distribution and a smoothed spectrogram.},
  author       = {Brynolfsson, Johan and Swärd, Johan and Jakobsson, Andreas and Sandsten, Maria},
  booktitle    = {Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on},
  issn         = {1520-6149},
  keyword      = {Time-frequency analysis,convex optimization,smooth},
  language     = {eng},
  pages        = {779--783},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Smooth Time-Frequency Estimation using Covariance Fitting},
  url          = {http://dx.doi.org/10.1109/ICASSP.2014.6853702},
  year         = {2014},
}