An Application on Time Series Clustering Based on Wavelet Decomposition and Denoising
Hongwei Guo, Yanchi Liu, Helan Liang, Xuedong Gao · 2008
Generally, the result of clustering cannot reflect the similarities of time series properly because of the disturbance of noises and details in time series. In this paper, a new approach to this problem based on wavelet decomposition and denoising is proposed. The approach has been tested and analyzed by Synthetic Control Chart Time Series from University of California,Irvine (UCI) knowledge discovery in databases (KDD).