### ASA 128th Meeting - Austin, Texas - 1994 Nov 28 .. Dec 02

## 4aUW12. A multiresolution, likelihood-based approach to pattern
classification with application to characterization and automated recognition
of marine mammal sounds.

**Thomas J. Hayward
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*Naval Res. Lab., Washington, DC 20375-5350
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A multiresolution, likelihood-based statistical approach is presented for
characterizing labeled classes of samples (e.g., measured time series or
time-frequency distributions of acoustic transients) and for classifying new
samples based on this statistical characterization. The labeled classes are
characterized by a histogram associated with a multiresolution decomposition of
the data in each class. Classification of a new sample is then performed by
calculating, for each labeled class, the conditional probability of the sample
given the statistics of that class. These conditional probabilities, which are
interpreted as relative likelihoods that the sample belongs to each of the
classes, are calculated in a recursive computation that proceeds from coarse to
fine resolution. A simple, efficient computer implementation using associative
arrays is presented. Successful classification of both time series and
time-frequency distributions of marine-mammal vocalizations is demonstrated
using relatively small numbers of labeled samples (~10 per class). [Work
supported by ONR.]