Abstract: Due to the length of uncertain time series and the uncertainty of values in each sample point,time complexity is very high when matching two uncertain time series．So the dimension reduction is the primary task to match fast for uncertain series．Now,always taking wavelet transform reduces dimension for uncertain time series,but the method does not consider the correlation between every sample points．We put forward a new method based on statistics and data correlation．It divides uncertain time series to probability dimension and time dimension and performs dimension reduction respectively in the two dimensions．We used a sampling point to represent the subsequent sampling points with high correlation in time dimension,and used large probability point to represent the adjacent small probability points in pro-bability dimension．Experimental results show that the compression ratio is remarkable when using the method to reduce uncertain time series．In addition,it can approximately recover the uncertain time series with reduced outcomes.

Key words: Time series,Uncertainty,Reduction,Statistics,Correlation