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A blind source separation technique using second-order statistics

机译:使用二阶统计量的盲源分离技术

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Separation of sources consists of recovering a set of signals of which only instantaneous linear mixtures are observed. In many situations, no a priori information on the mixing matrix is available: The linear mixture should be "blindly" processed. This typically occurs in narrowband array processing applications when the array manifold is unknown or distorted. This paper introduces a new source separation technique exploiting the time coherence of the source signals. In contrast with other previously reported techniques, the proposed approach relies only on stationary second-order statistics that are based on a joint diagonalization of a set of covariance matrices. Asymptotic performance analysis of this method is carried out; some numerical simulations are provided to illustrate the effectiveness of the proposed method.
机译:信号源的分离包括恢复仅观察到瞬时线性混合物的一组信号。在许多情况下,没有关于混合矩阵的先验信息:线性混合物应“盲目”处理。当阵列歧管未知或变形时,这通常发生在窄带阵列处理应用中。本文介绍了一种利用信号源时间相干性的新信号源分离技术。与其他先前报告的技术相比,所提出的方法仅依赖于基于一组协方差矩阵的联合对角化的平稳二阶统计量。对该方法进行渐近性能分析。提供了一些数值模拟,以说明该方法的有效性。

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