论文标题
空间上的盲源分离
Blind Source Separation over Space
论文作者
论文摘要
我们为Bachoc等人的盲源分离模型提出了一种新的估计方法。 （2020）。新的估计基于根据多个归一化空间局部协方差矩阵定义的正定义矩阵的特征分析，因此可以处理适中的高维随机场。即使特征 - 间隙衰减慢慢，估计的混合矩阵的一致性也以显式错误率建立。通过仿真和真实数据示例说明了所提出的方法。
We propose a new estimation method for the blind source separation model of Bachoc et al. (2020). The new estimation is based on an eigenanalysis of a positive definite matrix defined in terms of multiple normalized spatial local covariance matrices, and, therefore, can handle moderately high-dimensional random fields. The consistency of the estimated mixing matrix is established with explicit error rates even when the eigen-gap decays to zero slowly. The proposed method is illustrated via both simulation and a real data example.
