Title :
Using wavelet-based indices for detecting abrupt changes in signals
Author :
Allali, Mohamed ; DeBrunne, Victor
Author_Institution :
Dept. of Comput. Sci., Math. & Phys., Chapman Univ., Orange, CA, USA
Abstract :
A new method based on the wavelet transform (WT) to detect abrupt changes in nonstationary noisy signals is presented. We show that the wavelet transform combined with the short time Fourier transform (STFT) provides a more accurate index of stationarity than the STFT alone, especially for very noisy signals.
Keywords :
Fourier transforms; signal detection; signal processing; signal representation; wavelet transforms; STFT; abrupt changes; nonstationary noisy signals; short time Fourier transform; signal detection; signal processing; stationarity; wavelet transform; wavelet-based indices; Computer science; Fourier transforms; Mathematics; Signal processing; Signal resolution; Spectrogram; Time frequency analysis; Uncertainty; Wavelet coefficients; Wavelet transforms;
Conference_Titel :
Signals, Systems and Computers, 2001. Conference Record of the Thirty-Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-7147-X
DOI :
10.1109/ACSSC.2001.987019
