Title :
Multiscale detection of nonstationary signals
Author :
Krim, H. ; Drouiche, K. ; Pesquet, J.C.
Author_Institution :
Lab. des Signaux et Syst., Gif-Sur-Yvette, France
Abstract :
A statistical method for detecting and/or localizing nonstationarities in a process observed over a time interval T is presented. Stationarity is induced by taking a wavelet transform of the process. A parametric model is fitted to the result. The error incurred in fitting the model is shown to preserve the singularity manifested in the transform. The error is then used to establish a statistical detection test that is free of any prior knowledge about the class of signals being analyzed, and of any user input
Keywords :
signal detection; statistical analysis; wavelet transforms; multiscale detection; nonstationary signals; parametric model; singularity; statistical detection test; statistical method; time interval; wavelet transform; Filter bank; Parametric statistics; Radar tracking; Signal analysis; Signal detection; Signal processing; Signal resolution; Signal to noise ratio; Testing; Wavelet analysis;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1992., Proceedings of the IEEE-SP International Symposium
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-0805-0
DOI :
10.1109/TFTSA.1992.274224
