### ASA 129th Meeting - Washington, DC - 1995 May 30 .. Jun 06

## 2pSP1. A wavelet auditory model and noise suppression.

**Anthony Teolis
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*Naval Res. Lab., 4555 Overlook Ave., S.W., Bldg. 210, Washington, DC
20375-5000
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Based on a wavelet auditory model (WAM) of the mammalian auditory system,
discrete time-scale representations of acoustic signals which are inherently
robust to ``noise'' emerge. The model consists of the two main processes of (i)
a ``continuous'' wavelet transform with a causal analyzing wavelet determined
by a ``shark-fin''-shaped frequency response (cochlear filter), and (ii) a
specific and signal-dependent sampling of the wavelet transform. In general the
pattern of samples in the wavelet domain is irregular and determined at lower
frequencies by activity at higher frequencies. By analyzing the model in terms
of the theory of mathematical frames, it is shown that acoustic signals may be
fully recovered from their WAM representation through iterative reconstruction
algorithms. Noise is thought of as that portion of an acoustic signal which is
``incoherent'' with respect to the underlying WAM frame functions. Because
coherent energy is highly localized and incoherent (noise) energy is
necessarily scattered in the time-scale plane by the WAM frame representation,
wavelet shrinkage techniques provide powerful algorithms for noise suppression.
Several numerical examples of the noise suppression abilities of these
algorithms are presented in the paper.