Smooth Time-Frequency Estimation using Covariance Fitting
(2014) 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP 2014) 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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4588285
- author
- Brynolfsson, Johan LU ; Swärd, Johan LU ; Jakobsson, Andreas LU and Sandsten, Maria LU
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Time-frequency analysis, convex optimization, smooth
- host publication
- 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)
- conference location
- Florence, Italy
- conference dates
- 2014-05-04 - 2014-05-09
- 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
- 2016-04-01 13:50:14
- date last changed
- 2022-01-27 21:21:42
@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}}, keywords = {{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 = {{https://lup.lub.lu.se/search/files/3616907/4588294.pdf}}, doi = {{10.1109/ICASSP.2014.6853702}}, year = {{2014}}, }