Statistical hypothesis testing with time-frequency surrogates to check signal stationarity

An operational framework is developed for testing stationarity relatively to an observation scale. The proposed method makes use of a family of stationary surrogates for defining the null hypothesis of stationarity. As a further contribution to the field, we demonstrate the strict-sense stationarity of surrogate signals and we exploit this property to derive the asymptotic distributions of their spectrogram and power spectral density. A statistical hypothesis testing framework is then proposed to check signal stationarity. Finally, some results are shown on a typical model of signals that can be thought of as stationary or nonstationary, depending on the observation scale used.

• Type: Journal
• Year: 2010
• Where: ICASSP
• Authors: Cédric Richard, André Ferrari, Hassan Amoud, Paul Honeine, Patrick Flandrin, Pierre Borgnat
• Keywords: Hypothesis Testing Framework, ICASSP 2010, Observation Scale, Power Spectral Density, Signal Processing