Optimization of weighting factors for multiple window spectrogram of event-related potentials
EURASIP Journal on Advances in Signal Processing - Special issue on applications of time-frequency signal processing in wireless communications and bioengineering
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in theory and methods for nonstationary signal analysis
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Periodogram averaging with multiple windows can be used in spectrum analysis of nonstationary data. Usually, however, the windows for the subspectra are equally weighted in the estimate. In this correspondence, a criterion for the optimization of weighting factors is formulated as the average of normalized bias, variance, or mean square error in a certain frequency interval around a predefined peaked spectrum. The weighting factors are optimized using the peak matched multiple windows, the sinusoid multiple windows, and the discrete prolate spheroidal sequences