Title :
Wavelet band features
Author :
Loe, R.S. ; Jung, Ken ; Anderson, Kyle ; Shen, Sylvia ; Lawton, Wayne
Author_Institution :
Lockheed Res. Dev. Div., Palo Alto, CA, USA
Abstract :
Wavelet band features are used to classify transient acoustic signals produced by impulses. Wavelet band features of one-dimensional sampled signals are formed by concatenating moments of squared moduli of each subband resulting from recursive decomposition of the signal using a low-pass conjugate quadrature filter. Joint time-frequency constant- Q (single octave) localization of the subband decomposition is shown to be a consequence of the vanishing moments and smoothness properties of wavelets associated with the filter. The moments of squared moduli constitute robust shift-invariant measures of the interband and intraband energy distribution that provide low-dimensional feature vectors for classifying signals. Classification results based on moment features are compared to results based on the short-time Fourier transform (STFT)
Keywords :
acoustic signal processing; feature extraction; filtering and prediction theory; signal detection; time-frequency analysis; transients; underwater sound; wavelet transforms; interband energy distribution; intraband energy distribution; joint time-frequency constant-Q localisation; low-pass conjugate quadrature filter; moment features; one-dimensional sampled signals; robust shift-invariant measures; short-time Fourier transform; subband decomposition; transient acoustic signals; wavelet band features; Discrete wavelet transforms; Energy measurement; Filters; Fourier transforms; Robustness; Signal detection; Signal generators; Time frequency analysis; Underwater tracking; Wavelet transforms;
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.1992.274146
