Pattern Recognition via Observation Correlations

In some pattern recognition tasks multiple observations of an observation vector Y = {Y1, Y2, ..., YM} are available for each object and the covariances of the Yi are characteristic of the object. With the assistance of a model of the generating process for Y a theoretical basis for the comparison of the covariance matrices is developed. Measurements based on synthetic data support the theory, and an application to some speaker verification is given as an example.