【摘要】 传统的非负独立分量分析(ICA)算法假设源信号独立,通过对观测信号预白化得到Z,再找到旋转矩阵W,从而保证Y=W×Z为非负,但不适用于源信号相关程度较大的情况。本文在深入分析传统算法的基础上对传统算法进行了相应的改进,通过引入去相关矩阵R,对于即使相关程度较大的源信号也可以进行较好地分解。实验结果证明,改进后的算法简单有效。更多还原

【Abstract】 For the independent source S,the conventional nonnegative independent component analysis(ICA) algorithm obtains Z by prewhiting X,and finds rotation matrix W to ensure that Y=W×Z are nonnegative.But if the source S is correlative,the algorithm cannot work well.This paper improves the algorithm.By the decorrelation matrix R,the improved algorithm can decompose the sources well,even if the sources are highly correlative.Experimental results demonstrate that the improved algorithm is simple and efficient.更多还原