Optimization of Weighting Factors for Multiple Window Time-Frequency Analysis

In English 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.