METHODS AND APPARATUS FOR FEATURE RECOGNITION TIME SHIFT CORRELATION

摘要

Methods and apparatus for feature recognition time shift correlation are presented. An exemplary method includes the step of identifying a feature in an input data stream. A starting time associated with the identified feature relative to a boundary of the input data stream is stored (8). A time interval until the identified feature is next repeated in the input data stream is then measured (11). Next, the measured time interval is compared (13) to each of a set of valid interval values (14) for the identified feature. A difference is then calculated between the stored starting time and a starting time associated with the identified feature relative to a boundary of a reference data sequence when the measured time interval matches one of the valid interval values (16). The calculated difference determines an amount that the input data stream must be time-shifted (17) to achieve correlation with the reference data sequence.