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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
and
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
project
Statistical Signal Processing Group
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
2026-02-11 10:23:18
@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}},
}