基于距离相关的信源数目盲确定
Blind Determination of the Number of Sources Using Distance Correlation
摘要：
提出了一种新的盲估计噪声，线性混合源的数量。基于Székely et al.的距离相关性度量，我们定义了源的依赖性准则（SDC），从我们的估计产生。与大多数以前提出的估计不同，SDC估计利用了源和噪声的完全独立性，以及源的非高斯性（与噪声的高斯性相反），通过隐式使用高阶统计。这导致更稳健、弹性和稳定的估计w.r.t.混合矩阵和噪声协方差结构。实证模拟结果证明了这些优点，在与当前最先进的估计相比的优越性能之上。
英文摘要：
A novel blind estimate of the number of sources from noisy, linear mixtures is proposed. Based on Székely et al.'s distance correlation measure, we define the Sources' Dependency Criterion (SDC), from which our estimate arises. Unlike most previously proposed estimates, the SDC estimate exploits the full independence of the sources and noise, as well as the non-Gaussianity of the sources (as opposed to the Gaussianity of the noise), via implicit use of high-order statistics. This leads to a more robust, resilient and stable estimate w.r.t. the mixing matrix and the noise covariance structure. Empirical simulation results demonstrate these virtues, on top of superior performance in comparison with current state of the art estimates.
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