%0 Journal Article
%T ON WAVELET-BASED METHODS FOR HURST INDEX ESTIMATION OF SELF-SIMILAR TRAFFIC<br>自相似数据流的Hurst指数小波求解法分析
%A Li Yongli
%A Liu Guizhong
%A Wang Haijun
%A Shang Zhaowei
%A <br>李永利
%A 刘贵忠
%A 王海军
%A 尚赵伟
%J 电子与信息学报
%D 2003
%I 
%X Existing wavelet methods for the estimation of the Hurst parameter of self-similar traffic are systematically analyzed and examined. The effects of wavelet functions, vanishing moments and wavelet decomposition levels on the results of wavelet methods for acquiring the Hurst index are investigated via numerical experiments. Some useful conclusions are drawn on the relationship between the accuracy of the methods and the selection of the order of vanishing moments and the selection of wavelet functions.
%K Self-similarity
%K Traffic data
%K Vanishing moments
%K Hurst index
%K Wavelet<br>自相似
%K 数据流
%K Hurst指数
%K 小波
%K 消失矩
%K 网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=326045EB772DA4EC&yid=D43C4A19B2EE3C0A&vid=C5154311167311FE&iid=CA4FD0336C81A37A&sid=8C83C265AD318E34&eid=03F1579EF92A5A32&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=14&reference_num=10