The Symbolic Algorithm for Time Series Data Based on Statistic Feature

A new symbolic algorithm for Time Series Data Based on Statistic Feature is put forward in order to surmount the bugs with which SAX(Symbolic Aggregate Approximation) Algorithm can not describe time series information fully.This algorithm,differing from the SAX,considered the symbolic as vector,and Mean and variance from each subsequence were regarded as components by which its mean value and radiation degree are described respectively.Since it could provide more information described time series than SAX do,more accuracy result could be get when it is applied to time series data-mining.Its excellent behave.have been proved by a lot of experiments.