直接正交联合对角化盲分离算法

针对盲源分离问题，利用白化预处理后信号的二阶和高阶累积量矩阵具有正交联合对角化的结构性质，以及多个实对称矩阵具有相同特征向量即可同时正交对角化的实对称矩阵的特征分解的理论，提出一种基于部分累积量矩阵特征分解的直接正交联合对角化算法. 该算法仅需要部分累积量矩阵信息，从而大大降低计算过程中的存储量和计算量. 通过数值模拟，该算法和经典的JADE算法性能接近，可以有效地进行盲分离.

Direct Orthogonal Algorithm of Joint Diagonalization for Blind Source Separation

In blind source separation, the second-order and higher-order cumulant matrices of pre-whitened signals have the structure orthogonal joint diagonalization. In eigendecomposition theory, the real symmetry matrices with the same eigenvectors can simultaneous diagonalization. In this paper, a direct orthogonal joint diagonalization algorithm based on eigendecomposition of the cumulant matrices is proposed for blind source separation. In practical computation, we only need part of the cumulant matrices, so the storage and calculation will be greatly reduced. The numerical simulation results show that the performance of our algorithm close to the one of JADE, it is effective for blind source separation.