%0 Journal Article
%T Adaptive on-line algorithm based on independent component analysis<br>基于独立分量分析的自适应在线算法
%A LV Shu-ping
%A FANG Xing-jie
%A <br>吕淑平
%A 方兴杰
%J 计算机应用研究
%D 2010
%I 
%X ICA is an efficient signal processing method which arose in recent years, an important problem learning in adaptive ICA is opting learning step. According to variable step thinking, this paper defined similarity measure which described the state of signal separation, to measure the level of similarity between output components, and thus developed an improved adaptive line algorithm. Adjusting the learning step on the basis of traditions of degree of signal separation which was reflected by dependent measure, and established the nonlinear relation between learning step and similarity measure variation, and overcame the disadvantages of traditional algorithms in the channel variation circumstances in the process of adaptive step. Performance analysis and simulation results show that separative signal has better performance in convergence and steady.
%K data cleaning
%K approximately duplicate records
%K string matching
%K string similarity
%K edit distance<br>独立分量分析
%K 相似性测度
%K 学习步长
%K 性能指标
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=6184F8D6A388F216335FC8094FB088C9&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=708DD6B15D2464E8&sid=410E875F4AAF3771&eid=6F4EA96A1A1FAD1E&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10