Two Dimensional Processing Of Speech And Ecg Signals Using The Wigner-Ville Distribution

The Wigner-Ville Distribution (WVD) has been shown to be a valuable tool for the analysis of non-stationary signals such as speech and Electrocardiogram (ECG) data. The one-dimensional real data are first transformed into a complex analytic signal using the Hilbert Transform and then a 2-dimensional image is formed using the Wigner-Ville Transform. For speech signals, a contour plot is determined and used as a basic feature. for a pattern recognition algorithm. This method is compared with the classical Short Time Fourier Transform (STFT) and is shown, to be able to recognize isolated words better in a noisy environment. The same method together with the concept of instantaneous frequency of the signal is applied to the analysis of ECG signals. This technique allows one to classify diseased heart-beat signals. Examples are shown.

[1]  Harinath Garudadri,et al.  Identification of invariant acoustic cues in stop consonants using the Wigner distribution , 1987 .

[2]  T. Claasen,et al.  The aliasing problem in discrete-time Wigner distributions , 1983 .

[3]  Boualem Boashash,et al.  Patterns in Hilbert transforms and Wigner-Ville distributions of electrocardiogram data , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[4]  Boualem Boashash,et al.  Wigner-Ville analysis of time-varying signals , 1982, ICASSP.

[5]  S. Kay,et al.  On the optimality of the Wigner distribution for detection , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  J. Mayer,et al.  On the Quantum Correction for Thermodynamic Equilibrium , 1947 .

[7]  August W. Rihaczek,et al.  Signal energy distribution in time and frequency , 1968, IEEE Trans. Inf. Theory.

[8]  Dennis Gabor,et al.  Theory of communication , 1946 .

[9]  H A Fozzard,et al.  AZTEC, a preprocessing program for real-time ECG rhythm analysis. , 1968, IEEE transactions on bio-medical engineering.