Higher order evolutionary spectral analysis

Abstract

Power Spectral Density of a signal is calculated from the second order statistics and provides valuable information for the characterization of stationary signals. This information is only sufficient for Gaussian and linear processes. Whereas, most real-life signals, such as biomedical, speech, and seismic signals may have non-Gaussian, non-linear and non-stationary properties. Higher Order Statistics (HOS) are useful for the analysis of such signals. Time-Frequency (TF) analysis methods have been developed to analyze the time-varying properties of non-stationary signals. In this work, we combine the HOS and the TF approaches, and present a method for the calculation of a Time-Dependent Bispectrum based on the positive distributed Evolutionary Spectrum.