BLIND SOURCE SEPARATION FOR FMRI SIGNALS USING A NEW INDEPENDENT COMPONENT ANALYSIS ALGORITHM
新的独立成分分析算法实现功能磁共振成像信号的盲分离

In order to separate independent components (task-related signal and other noises) from functional magnetic reasonance imaging(fMRI)signals, a new independent component analysis algorithm was used. In contrast to fastICA, the algorithm reduced computation and raised speed of operation. It also separated independent components from fMRI signals very well.