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   -> Volume 6, Issue 9

Preprint: Signal detection in underwater sound using wavelets
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mafs (

PostPosted: Wed Sep 03, 1997 7:20 am    
Subject: Preprint: Signal detection in underwater sound using wavelets
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#8 Preprint: Signal detection in underwater sound using wavelets

Dear readers,

The following preprint is available:

Title: Signal Detection in Underwater Sound Using Wavelets.

Authors: T.C. Bailey, T. Sapatinas, K.J. Powell and W.J. Krzanowski


This paper considers the use of wavelet methods in relation to a
common signal processing problem, that of detecting transient features
in sound recordings which contain interference or distortion. In this
particular case, the data are various types of underwater sounds, and
the objective is to detect intermittent departures (potential
`signals') from the background sound environment in the data
(`noise'), where the latter may itself be evolving and changing over
time. We develop an adaptive model of the background interference,
using recursive density estimation of the joint distribution of
certain summary features of its wavelet decomposition. Observations
which are considered to be outliers from this density estimate at any
time are then flagged as potential `signals'. The performance of our
method is illustrated on artificial data, where a known `signal' is
contaminated with simulated underwater `noise' using a range of
different signal-to-noise ratios, and a `baseline' comparison is made
with results obtained from a relatively unsophisticated, but commonly
used, time-frequency approach. A similar comparison is then reported
in relation to the more significant problem of detecting various types
of dolphin sound in real conditions.

Note: To appear in Journal of the American Statistical Association,
Applications and Case Studies.

The preprint is available at:

The figures for this paper are available at:

Dr. Theofanis Sapatinas
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