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Optimal Multiple Window Time-Frequency Analysis of Locally Stationary Processes

Sandsten, Maria LU and Wahlberg, Patrik LU (2004) 12th European Signal Processing Conference EUSIPCO, 2004 p.1781-1784
Abstract
This paper investigates the multiple windows of the mean squared error optimal time-frequency kernel for estimation of the Wigner-Ville spectrum. The kernel is optimal for a certain locally stationary process where the covariance function is determined by two one-dimensional Gaussian functions. The multiple windows are obtained as the eigenvectors of the rotated time-lag estimation kernel. The spectrograms from the different windows are weighted with the eigenvalues and the resulting multiple window spectrogram is an estimate of the optimal smoothed Wigner-Ville spectrum.
Please use this url to cite or link to this publication:
author
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organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
12th European Signal Processing Conference, EUSIPCO 2004
pages
1781 - 1784
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
12th European Signal Processing Conference EUSIPCO, 2004
conference location
Vienna, Austria
conference dates
2004-09-06 - 2004-09-10
external identifiers
  • scopus:84979894088
ISBN
978-320000165-7
language
English
LU publication?
yes
additional info
The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Mathematical Statistics (011015003), Department of Electroscience (011041000)
id
a32d11cd-a20c-4a16-99d7-8acf20314ec3 (old id 627403)
alternative location
http://ieeexplore.ieee.org/document/7079735/
date added to LUP
2016-04-04 14:02:46
date last changed
2022-01-30 08:43:26
@inproceedings{a32d11cd-a20c-4a16-99d7-8acf20314ec3,
  abstract     = {{This paper investigates the multiple windows of the mean squared error optimal time-frequency kernel for estimation of the Wigner-Ville spectrum. The kernel is optimal for a certain locally stationary process where the covariance function is determined by two one-dimensional Gaussian functions. The multiple windows are obtained as the eigenvectors of the rotated time-lag estimation kernel. The spectrograms from the different windows are weighted with the eigenvalues and the resulting multiple window spectrogram is an estimate of the optimal smoothed Wigner-Ville spectrum.}},
  author       = {{Sandsten, Maria and Wahlberg, Patrik}},
  booktitle    = {{12th European Signal Processing Conference, EUSIPCO 2004}},
  isbn         = {{978-320000165-7}},
  language     = {{eng}},
  pages        = {{1781--1784}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Optimal Multiple Window Time-Frequency Analysis of Locally Stationary Processes}},
  url          = {{http://ieeexplore.ieee.org/document/7079735/}},
  year         = {{2004}},
}