Title :
Using Malvar wavelets for transient detection
Author :
Ravier, P. ; Amblard, P.O.
Author_Institution :
CNRS, St. Martin d´´Heres, France
Abstract :
This paper is devoted to the detection of transient acoustic signals in very low signal-to-noise ratio contexts. The proposed algorithm uses the adaptive Malvar wavelet transform. It leads to a partition of the signal which is “optimal” according to a criteria that tests the Gaussian nature of the segments. A statistic based on the kurtosis is computed from this segmentation
Keywords :
Gaussian processes; acoustic noise; acoustic signal detection; adaptive signal detection; transient analysis; underwater sound; wavelet transforms; Gaussian nature; adaptive Malvar wavelet transform; kurtosis; partition; segmentation; statistic; transient acoustic signals; transient detection; very low signal-to-noise ratio context; Acoustic signal detection; Acoustic testing; Gaussian noise; Higher order statistics; Partitioning algorithms; Reactive power; Signal to noise ratio; Underwater acoustics; Underwater tracking; Wavelet transforms;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on
Conference_Location :
Paris
Print_ISBN :
0-7803-3512-0
DOI :
10.1109/TFSA.1996.547455
