欠定模型下源信号及混合矩阵动态变化时的盲分离

提出了一种改进的两步法实现欠定模型下信源及信道动态变化时的盲分离。首先通过实时的观测信号,基于稀疏域二维最小偏差角判断混合矩阵的变化时刻,进而估计动态变化的混合矩阵并获得实时的源数目;再采用基于伪提取矢量的方法恢复动态的源信号。在源信号的恢复中,使用常规的基于线性规划的欠定盲分离方法,以进行对比。结果表明,该方法能处理信源及信道动态变化时的欠定盲分离,并且分离速度比基于线性规划的方法快数十倍。仿真结果表明了该算法的良好性能。

Underdetermined Blind Source Separation of Dynamic Sources and Mixing Matrix

A new kind of improved two-step approach for underdetermined blind separation of dynamic sources and mixing matrix is proposed in the paper. Firstly, the change time of the mixing matrix is estimated based on planar minimum offset angle of sparse domain. The mixing matrix is then estimated and the dynamic number of sources is determined. Secondly, the source signals are recovered by pseudo extraction vector method, and the underdetermined blind separation of source signals is achieved by applying linear programming method. Results show that not only the proposed method can accomplish underdetermined blind separation of dynamic sources and mixing matrix but also its velocity of separation is ten times of the methods based on linear programming.