%0 Journal Article
%T Online bootstrap monitoring of the stationarity for a class of heavy tailed random signals<br>一类厚尾随机信号平稳性的在线bootstrap监测
%A CHEN Zhan-shou
%A TIAN Zheng
%A <br>陈占寿
%A 田铮
%J 控制理论与应用
%D 2010
%I 
%X Impulse noise makes random signals occur heavy tails. For the online heavy tailed random signal with symmetrically distributed stable noise, we propose a kernel weighted variance ratio procedure to sequentially detect its stationarity. The asymptotic distribution of the monitoring statistic under nonstationary null hypothesis is derived, and its consistency is proved. In order to determine the critical values of the monitoring statistic and avoid the estimation of the tail index, we propose a bootstrap resampling method. Simulations and analysis of two groups of real data validate the proposed procedure.
%K online monitoring
%K heavy tailed random signal
%K staionarity
%K bootstrap<br>在线监测
%K 厚尾随机信号
%K 平稳性
%K bootstrap
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=8CF6AFC985083D0A7CA6E422D6EBC8C6&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=DF92D298D3FF1E6E&sid=3C5A0072CBF0FE42&eid=502AE9EE93CAADD7&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=17