基于四阶累积张量方法的欠定盲源信号分离

Fourth-Order Cumulant of Tensor Decomposition Method for Blind Identification of Underdetermined Separation

针对瞬时欠定盲源信号分离问题,提出一种四阶累积张量分解算法.首先构建观察信号四阶累积协方差,依据源信号具有相互独立且均值为零的性质,对累积协方差化简并扩展到张量域,得到四阶累积张量.采用分层交替最小二乘算法对四阶累积张量进行非负库克分解,求得非负库克模型的参数,同时获得非负混合矩阵并求其伪逆,最终估计出源信号.选用真实的语音信号和生物信号进行仿真实验,结果表明该方法提高了源信号和非负混合矩阵的估计性能.

This paper proposes a fourth order cunmulant of tensor decomposition method to solve the problem for blind idenfitication of underdetermined separation.First, the fourth order cumulant of covariance is constructed based on observe signals. By assuming that the source signals are independent,and are of zero mean, the hierarchical alternating least squares method is used to decompose fourth order cumulant of tensor into the nonnegative Tucker. Then, the mixture matrix is acquired by the parameters of nonnegative Tucker model. The source is also acquired by solving the pseudo-inverse of mixture matrix. Finally, by using the speech signals and the biomedical signals, two numerical examples are conducted to demonstrate the effectiveness of the proposed method.