Optimization of Weighting Factors for Multiple Window Time-Frequency Analysis

Research output: Contribution to conferencePaper, not in proceeding

Abstract

This paper concerns the optimal weighting factors for multiple
window spectrogram estimation of different stationary
and non-stationary processes. The choice of windows are of
course important but the weighting factors in the average of
the different spectrograms are as important. The criterion for
optimization is the normalized mean square error where the
normalization factor is the spectrogramestimate. This means
that the unknown weighting factors will be present in the numerator
as well as in the denominator. A quasi-Newton algorithm
is used for the estimation. The optimization is compared
for a number of well known sets of multiple windows
and the results show that the number as well as the shape of
the windows are important factors for a small mean square
error.

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Subject classification (UKÄ) – MANDATORY

  • Probability Theory and Statistics
Original languageEnglish
Pages2283-2287
StatePublished - 2009
Publication categoryResearch
Peer-reviewedYes
Event17th European Signal Processing Conference, 2009: EUSIPCO 2009 - Glasgow, Scotland, Glasgow, Scotland, United Kingdom
Duration: 2009 Aug 242009 Aug 28
Conference number: 17

Conference

Conference17th European Signal Processing Conference, 2009
CountryUnited Kingdom
CityGlasgow, Scotland
Period2009/08/242009/08/28