Optimal Multiple Window Time-Frequency Analysis of Locally Stationary Processes

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

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.

Details

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Probability Theory and Statistics
Original languageEnglish
Title of host publication12th European Signal Processing Conference, EUSIPCO 2004
PublisherIEEE--Institute of Electrical and Electronics Engineers Inc.
Pages1781-1784
ISBN (Print)978-320000165-7
Publication statusPublished - 2004
Publication categoryResearch
Peer-reviewedYes
Event12th European Signal Processing Conference EUSIPCO, 2004 - Vienna, Vienna, Austria
Duration: 2004 Sep 62004 Sep 10

Conference

Conference12th European Signal Processing Conference EUSIPCO, 2004
CountryAustria
CityVienna
Period2004/09/062004/09/10

Bibliographic note

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)