[show abstract][hide abstract] ABSTRACT: In this paper, we propose a novel time-frequency distribution (TFD) for the analysis of multi-component signals. In particular, we use synthetic as well as real-life speech signals to prove the superiority of the proposed TFD in comparison to some existing ones. In the comparison, we consider the cross-terms suppression and the high energy concentration of the signal around its instantaneous frequency (IF).
[show abstract][hide abstract] ABSTRACT: The paper presents a quantitative comparison study of some time-frequency distributions i.e. (TFDs). The comparison is in terms of a criterion known as the Renyi measure. The assessment of the TFDs is accomplished by evaluating the Rényi measure which yields the best time-frequency resolu-tion. We show, using synthetic as well as real-life data, that a recently proposed TFD outperforms existing TFDs. In particular, we show that this proposed TFD presents a high time-frequency resolution while suppressing the undesir-able cross-terms.