Blind Source Separation Based on FastICA
暂无分享,去创建一个
Blind source separation has common considerable attention from the signal processing community and the neural network community. It is becoming a hot topic. The independent component analysis (ICA) is a new method of blind source separation which is developing in these years. In this paper,a fast algorithm of blind source separation based on ICA is introduced,the result of experiment show that Fast independent component analysis (FastICA) can separate every independent component effectively , It is more flexible and robust than those using the conventional independent component analysis methods.
[1] Erkki Oja,et al. Independent component analysis: algorithms and applications , 2000, Neural Networks.
[2] Jian-Huang Lai,et al. Face representation using independent component analysis , 2002, Pattern Recognit..