Optimization of Weighting Factors for Multiple Window TimeFrequency Analysis
(2009) 17th European Signal Processing Conference, 2009 p.22832287 Abstract
 This paper concerns the optimal weighting factors for multiple
window spectrogram estimation of different stationary
and nonstationary 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 quasiNewton algorithm
is used for the estimation. The optimization is compared
for a number of well known sets of multiple... (More)  This paper concerns the optimal weighting factors for multiple
window spectrogram estimation of different stationary
and nonstationary 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 quasiNewton 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. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/record/1515155
 author
 Sandsten, Maria ^{LU} and Sandberg, Johan ^{LU}
 organization
 publishing date
 2009
 type
 Contribution to conference
 publication status
 published
 subject
 pages
 2283  2287
 conference name
 17th European Signal Processing Conference, 2009
 external identifiers

 Scopus:84863757263
 language
 English
 LU publication?
 yes
 id
 7fe3d97451b0453bb5b87feea367c53f (old id 1515155)
 alternative location
 http://www.eurasip.org/Proceedings/Eusipco/Eusipco2009/contents/papers/1569188810.pdf
 date added to LUP
 20091214 11:13:21
 date last changed
 20161013 05:01:03
@misc{7fe3d97451b0453bb5b87feea367c53f, abstract = {This paper concerns the optimal weighting factors for multiple<br/><br> window spectrogram estimation of different stationary<br/><br> and nonstationary processes. The choice of windows are of<br/><br> course important but the weighting factors in the average of<br/><br> the different spectrograms are as important. The criterion for<br/><br> optimization is the normalized mean square error where the<br/><br> normalization factor is the spectrogramestimate. This means<br/><br> that the unknown weighting factors will be present in the numerator<br/><br> as well as in the denominator. A quasiNewton algorithm<br/><br> is used for the estimation. The optimization is compared<br/><br> for a number of well known sets of multiple windows<br/><br> and the results show that the number as well as the shape of<br/><br> the windows are important factors for a small mean square<br/><br> error.}, author = {Sandsten, Maria and Sandberg, Johan}, language = {eng}, pages = {22832287}, title = {Optimization of Weighting Factors for Multiple Window TimeFrequency Analysis}, year = {2009}, }