AN ITERATIVE ALGORITHM OF INDEPENDENT COMPONENT ANALYSIS AND THE EXPERIMENT RESULTS
一种独立分量分析的迭代算法和实验结果

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.