Stationarity index for abrupt changes detection in the time-frequency plane

This paper presents a new method based on time frequency representations (TFRs) for detecting abrupt changes in non-stationary noisy signals, Stationarity indices (SIs), based on different distance measures between TFRs, are defined and a comparison of the performances is performed using ROC curves and statistical properties. Two sets of signals are specially studied here: signals presenting very short segments and nonstrictly stepwise stationary signals. For these signals, classical methods based on autoregressive (AR) spectral estimators are often unsuccessful.