%0 Journal Article
%T Overdetermined Blind Source Separation Based on Singular Value Decomposition<br>基于奇异值分解的超定盲信号分离
%A Zhu Xiao-long
%A Zhang Xian-da
%A <br>朱孝龙
%A 张贤达
%J 电子与信息学报
%D 2004
%I 
%X The problem of overdetermined Blind Source Separation (BSS) where there are more mixtures than sources is considered. Beginning with the Singular Value Decomposition (SVD) of the separation matrix, a cost function is presented based on Independent Component Analysis (ICA), and then the ordinary gradient learning algorithm is developed. Secondly, resorting to the relative gradient, it is shown that the natural gradient learning algorithm for overdetermined BSS has the same form as that for usual complete BSS, which is verified by simulation results.
%K Blind source separation
%K Independent component analysis
%K Relative gradient
%K Natural gradient
%K Singular Value Decomposition (SVD)<br>盲信号分离
%K 独立分量分析
%K 相对梯度
%K 自然梯度
%K 奇异值分解
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=1DF4ECC0AFA83888&yid=D0E58B75BFD8E51C&vid=96C778EE049EE47D&iid=38B194292C032A66&sid=5FF9F4F7CB1800C7&eid=5957D6E0A50D26B5&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=8&reference_num=14