%0 Journal Article
%T Underdetermined Blind Source Separation Algorithm Based on Normal Vector of Hyperplane<br>基于超平面法矢量的欠定盲信号分离算法
%A XIAO Ming
%A XIE Sheng-Li
%A FU Yu-Li
%A <br>肖明
%A 谢胜利
%A 傅予力
%J 自动化学报
%D 2008
%I 
%X Discussion of blind signal separation problem under underdetermined case(i.e.,the case of less observed signals than sources)is presented.First,a formula to calculate the normal vector of any hyperplane is given and a mixing matrix recovery algorithm based on the normal vector of any hyperplane is proposed.Second,for audio signal,k-source intervals are introduced and a method to detect them is proposed.So,the algorithms under the k-SCA condition are extended to blind non-sparse signal separation.To reconstruct the sources,a new algorithm is proposed to simplify the l~1-norm solution.Several experiments demonstrate the performance of the proposed algorithm.
%K Underdetermined blind signal separation(BSS)
%K sparse component analysis(SCA)
%K hyperplane clustering
%K normal vector
%K k-source interval<br>欠定盲信号分离(BSS)
%K 稀疏成分分析(SCA)
%K 超平面聚类
%K 法矢量
%K k源区间
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=3EC0AB98980A9C6E2FF502300E59CFD4&yid=67289AFF6305E306&vid=339D79302DF62549&iid=0B39A22176CE99FB&sid=E22B6B8FE86DD8F9&eid=EB552E4CFC85690B&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=16