Title :
Pattern Recognition via Observation Correlations
Author :
Bogner, Robert E.
Author_Institution :
Department of Electrical Engineering, University of Adelaide, Adelaide, Australia.
fDate :
3/1/1981 12:00:00 AM
Abstract :
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.
Keywords :
Acoustic testing; Area measurement; Covariance matrix; Displays; Eigenvalues and eigenfunctions; Mechanical factors; Particle measurements; Pattern recognition; Tongue; Visualization; Covariance matrices; distance measures; eigenvector modules; orthogonal components; pattern recognition; spectral covariances; talker identification; talker verification;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1981.4767070
