Abstract: According to the information Theory, we introduce a method with which we can quantitatively calculate the mutual information of two systems S and Q,i.e.I(S; Q)=∑P(s_i,q_j).log[P(s_i,q_j)/P(s_i)P(q_j)].The predictability of the data of a system was analyzed and the optimal prediction precision was obtained by the computing results of the mutual information between the one dimensional time series and its time delayed series from the time period systems,chaotic systems and random systems. The dissimilarity of the data of a system was estimated by the computing regular of the mutual information between the two dimensional time series from time period systems, chaotic systems and randoms systems,thus the waive of releasing the work could be avoided. Compared with the cross correlation function,the mutual information can quantitatively show the relation between the two time series.

Key words: time series, data predictability, data dissimilarity, mutual information