METHOD AND DEVICE FOR CLASSIFICATION OF A FIRST TIME SEQUENCE AND A SECOND TIME SEQUENCE

摘要

Time sequences are examined with respect to their statistical dependence and neuronal networks are trained in such a way that time sequence probability densities caused by a each neuronal network are modelled. Neuronal networks are used to determine surrogate time sequences and variables are determined for the statistical dependence of time sequence samples and surrogate time sequence samples. Said variables are compared with each other and the dynamic performance of each basic time sequence is examined as to whether it is described by a Markhov process in the order of (n1,..., nN).