Published March 15, 2010
| Version v1
Conference paper
Statistical hypothesis testing with time-frequency surrogates to check signal stationarity
- Others:
- Laboratoire Hippolyte Fizeau (FIZEAU) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS)
- Laboratoire Modélisation et Sûreté des Systèmes (LM2S) ; Institut Charles Delaunay (ICD) ; Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)
- Laboratoire de Physique de l'ENS Lyon (Phys-ENS) ; École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL) ; Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)
- ANR-07-BLAN-0191,StaRAC,Stationnarité relative et approches connexes(2007)
Description
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.
Abstract
International audience
Additional details
- URL
- https://hal-ens-lyon.archives-ouvertes.fr/ensl-00476017
- URN
- urn:oai:HAL:ensl-00476017v1
- Origin repository
- UNICA