Optimization of quadratic time-frequency distributions using the local Rényi entropy information

This paper presents two TFD optimization schemes, extending an optimization method so far limited to the spectrogram. The first method is focused on the enhancement of the spectrogram concentration, by an adaptive realization of the S-method TFD which prevents cross-terms generation. The second approach, a generalization of the first one to the Quadratic class of TFDs, operates on a set of TFDs with different kernel parameters, selecting for each time instant the best performing one. Both methods use an entropy-based criterion for concentration enhancement, and a here-proposed method for the detection of cross-terms. The combination of the two criteria allows us to generate optimal TFDs, i.e. TFDs with highly concentrated components, but at the same time avoiding the appearance of undesirable cross-terms in the resulting TFD. HighlightsTwo TFD adaptive optimization schemes are proposed.An entropy criterion and a method for detection of cross-terms are combined.TFDs with highly concentrated components and no cross-terms are obtained.

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