一种新的联合块对角化卷积盲分离时域算法

A new joint block diagonalization time-domain algorithm for convolutive blind separation

提出一种基于高阶累积量联合块对角化的时域算法求解卷积混合盲信号分离问题。引入白化处理,将混叠矩阵转变成酉矩阵,混合信号转变为互不相关的,进而计算出其对应的一系列高阶累积量矩阵,通过最小化代价函数来实现高阶累积量矩阵联合块对角化的目的,在时域中解决超定卷积盲分离问题。实验表明,相比于经典的自然梯度算法,所提方法的分离精度更高,且运算速度也更快。

This paper proposes a new time-domain joint block diagonalization algorithm based on the high-order cumulant for the blind source separation of convolutive mixtures. This paper adopts the whitening procedure to transform the mixing matrix into an unitary matrix. Computing the high-order cumulant matrixes of the mixing signals whitened, which can be transformed into block diagonal matrixes through minimizing the cost function, Simulations results illustrate that, the new method outperforms the classic natural gradient method in separation precision and operation speed, and can he efficiently applied to the blind source separation of convolutive mixtures.