A time-frequency distribution of Cohen´s class with a compound kernel and its application to speech signal processing

Time-frequency distributions belonging to Cohen´s class have been discussed in deterministic nonstationary signal processing. The Wigner-Ville distribution is the first to be proposed among the class and is most widely studied and applied in the various fields. However, one of the main difficulties with the Wigner-Ville distribution is that it indicates spurious values in the intensity due to interference particularly prevalent for multicomponent signals. The authors propose a new type kernel function that is the product of the Choi-Williams kernel and the Margenau-Hill kernel. Specific types of signals: sinusoidal signals, chirp signals, and others are analyzed using the new distribution in comparison with the results by the Wigner-Ville and the Choi-Williams distributions. The present distribution does not indicate spurious intensity in the regions where the other two distributions do. In the authors´ distribution, the spurious values are transferred to places where one would expect the signal´s inherent intensity at least for a signal of pure sine waves. Thus correct values of the signal´s intensity are slightly modulated due to cross talk. The three distributions are also compared numerically for these signals and for speech signals to show the advantages of the present distribution