We propose a new estimation method for the spatial blind source separation model. The new estimation is based on an eigenanalysis of a positive definite matrix defined in terms of multiple 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.
翻译:我们为空间盲源分离模型提出了新的估计方法。新的估计基于对以多个空间局部共变矩阵为定义的正确定矩阵的精密分析,因此可以处理中度高维随机字段。估计混合矩阵的一致性以明确的误差率确定,即使eigen-gap衰减到零。提议的方法通过模拟和真实的数据示例加以说明。