基于独立成分分析的脑电伪迹消除方法

A Method of Removal Artifacts Based on Independent Component Analysis

独立成分分析 (ICA)是统计信号处理中的一项新技术 ,用来从混合信号中提取具有统计独立性的成分 ,基于固定点快速算法 ,从脑电 (EEG)信号中消除眼电 (EOG)伪迹信号 ,并给出了实验结果 ,实验结果表明该算法具有较好的性能和实用性。

Independent Composition Analysis (ICA) is a new technique in signal processing to extract statistically independent components from an observed multidimensional mixture of signals. A fast fixed-point algorithm that is capable of separating complex values, linearly mixed source signal is proposed and (EOG) Artifacts shows its computational efficiency in removing EOG Artifacts from electroencephalography (EEG).