%0 Journal Article
%T A class of unbiased identification for inverse system with input noises<br>一类有输入噪声扰动的逆系统无偏参数辨识算法研究
%A liu qing
%A Yue Dong
%A <br>刘清
%A 岳东
%J 控制理论与应用
%D 2009
%I 
%X In identifying the inverse system, the input is the output from the original system. This signal is corrupted by noises with unknown variance. When the ordinary least-squares method is applied to estimate the parameters of the inverse system, the estimates turn out to be biased. A new identification algorithm for bias compensation is proposed. Therein, the noise variance of the inverse system input is first estimated using the wavelet transform, and then, a recursive least-squares method with bias-elimination is used to estimate the parameters of the inverse system. Thus, the proposed algorithm does not require the input signal to be the white noise with a zero mean. Since the computation is recursive, it can be implemented online for estimating parameters of the inverse system. Experimental results show that the approach is effective.
%K inverse system
%K parameter identification
%K input noise
%K bias-eliminated<br>逆系统
%K 参数辨识
%K 输入噪声
%K 偏差消除
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=7F7661D640F1B6CA780F2C6FC320851C&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=9CF7A0430CBB2DFD&sid=D7513DBF373F2B6C&eid=78996380F3108204&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=7