New divergence measures are introduced for change detection and discrimination of stochastic signals (time series) on the basis of parametric filtering — a technique that combines parametric linear filtering with correlation characterization. The sensitivity of these divergence measures is investigated using local curvatures under additive and multiplicative spectral departure models. It is fou...