## 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.

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.

Original language | English |
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Pages | 2283-2287 |

Publication status | Published - 2009 |

Event | 17th European Signal Processing Conference, 2009: EUSIPCO 2009 - Glasgow, Scotland, Glasgow, Scotland, United Kingdom Duration: 2009 Aug 24 → 2009 Aug 28 Conference number: 17 |

### Conference

Conference | 17th European Signal Processing Conference, 2009 |
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Country/Territory | United Kingdom |

City | Glasgow, Scotland |

Period | 2009/08/24 → 2009/08/28 |

## Subject classification (UKÄ)

- Probability Theory and Statistics