%0 Journal Article
%T Minimum error estimation using wavelet for time series similarity search<br>对时间序列查询的最优小波误差估计
%A WANG Lu-shan
%A LIU Bing
%A LIU Yong
%A <br>王露珊
%A 刘兵
%A 刘勇
%J 计算机应用
%D 2007
%I 
%X Wavelet transform is used as a dimensionality reduction method to permit efficient similarity search over high-dimensional time series data. The traditional algorithms use the first k wavelet coefficients as an approximation of the original time series. But sometimes choosing the first k coefficients is not the best when approximating the original time series. Perhaps choosing other k wavelet coefficients is better than choosing the first k. The theorem was given to better approximate the original time series set. The main idea of the theorem was to choose the k columns of the wavelet sequences set which had the maximum square sum. The experiments show that it can better reduce the relative error compared with original algorithms.
%K time series
%K wavelet transform
%K error estimation<br>时间序列
%K 小波变换
%K 误差估计
%K 时间序列
%K 序列相似性查询
%K 最优小波
%K 误差估计
%K search
%K similarity
%K time
%K series
%K wavelet
%K error
%K estimation
%K 相对误差
%K 结果
%K 实验
%K 列平方
%K 数集
%K 小波系
%K 定理
%K 相关
%K 列集
%K 近似估计
%K 选择
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD27430512FE0E51D7039D2BF5&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=38B194292C032A66&sid=18F040DBCB74FFF9&eid=03EE8EDD44A3D4BE&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=22