Methods for recognition of multidimensiional patterns cross-reference to related applications

摘要

A method implemented by a computer for recognition of multidimensional patterns, represented by multidimensional arrays of multidimensional vectors which are derived from data collected from speech, images, video, signals, static physical entities or moving physical entities. The recognition is based on classification into pattern classes. For the classification the invention provides efficient methods for the computation of similarity measures between input patterns and stored patterns. Usually, input patterns are acquired by sensors and their class is unknown. They are classified by finding the stored pattern class with the highest similarity measure to the input pattern. For speech and image recognition, the methods provide additional innovations which improve the reliability. Speech is represented by one dimensional arrays of multidimensional vectors. These arrays represent continuous speech our methods have novel means for separating the signal into words and phonemes. New penalty functions improve false positives and correct recognition rates. Similar approach is used for images and video.