Method for time series clustering based on Normal matrix
一种基于Normal矩阵的时间序列聚类方法*

This paper presented a method for time series clustering based on the spectral bisection method of Normal matrix. The algorithm transformed time series data into vector forms firstly, calculated the similarity between any pairs of time series and constructed complex network. Then the complex network would be divided into communities by using of the method of Normal matrix. The time series were clustered in terms of the results of partitioning network. Finally, in order to verify the feasibility and effectiveness of the presented method, analyzed the real world stock time series, compared other methods on two real datasets and obtained the reasonable results.