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Optimization of Weighting Factors for Multiple Window Time-Frequency Analysis

Sandsten, Maria LU and Sandberg, Johan LU (2009) 17th European Signal Processing Conference, 2009 p.2283-2287
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
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
7fe3d974-51b0-453b-b5b8-7feea367c53f (old id 1515155)
alternative location
http://www.eurasip.org/Proceedings/Eusipco/Eusipco2009/contents/papers/1569188810.pdf
date added to LUP
2009-12-14 11:13:21
date last changed
2017-01-01 08:17:29
@misc{7fe3d974-51b0-453b-b5b8-7feea367c53f,
  abstract     = {This paper concerns the optimal weighting factors for multiple<br/><br>
window spectrogram estimation of different stationary<br/><br>
and non-stationary 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 quasi-Newton 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        = {2283--2287},
  title        = {Optimization of Weighting Factors for Multiple Window Time-Frequency Analysis},
  year         = {2009},
}