%0 Journal Article
%T AN ITERATIVE ALGORITHM OF INDEPENDENT COMPONENT ANALYSIS AND THE EXPERIMENT RESULTS<br>一种独立分量分析的迭代算法和实验结果
%A ZHOU Wei-dong
%A JIA Lei
%A LI Ying-yuan
%A <br>周卫东
%A 贾磊
%A 李英远
%J 生物物理学报
%D 2002
%I 
%X An independent component analysis (ICA) method in blind source separation (BSS) is introduced. An objective function is given based on information theory. A fast iterative ICA algorithm is derived by optimizing the function. In contrast to most blind source separation algorithms, the method does not need to calculate the higher order statistics of signals, and converges fast. The proposed method is verified by computer-simulating with biological signals such as clinical electroencephalograph (EEG) signal and other kind of signals.
%K Blind source separation(BSS)
%K Independent component analysis(ICA)
%K Artificial neural network(ANN)
%K Negentropy<br>迭代算法
%K 盲信源分离
%K 独立分量分析
%K 人工神经网络
%K 负熵
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=90BA3D13E7F3BC869AC96FB3DA594E3FE34FBF7B8BC0E591&jid=E0C9D9BBED813D6674AC13E942EAC86D&aid=42E18276A7236321&yid=C3ACC247184A22C1&vid=13553B2D12F347E8&iid=CA4FD0336C81A37A&sid=11B4E5CC8CDD3201&eid=BFE7933E5EEA150D&journal_id=1000-6737&journal_name=生物物理学报&referenced_num=9&reference_num=10