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Convergence of empirical spectral distributions of large dimensional quaternion sample covariance matrices

机译:大型四元数样本协方差矩阵的经验光谱分布的收敛性

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摘要

In this paper, we establish the limit of empirical spectral distributions of quaternion sample covariance matrices. Motivated by Bai and Silverstein (Spectral analysis of large dimensional random matrices, Springer, New York, 2010) and Marenko and Pastur (Matematicheskii Sb, 114:507-536, 1967), we can extend the results of the real or complex sample covariance matrix to the quaternion case. Suppose is a quaternion random matrix. For each , the entries are independent random quaternion variables with a common mean and variance . It is shown that the empirical spectral distribution of the quaternion sample covariance matrix converges to the Marenko-Pastur law as , and (0 + infinity).).
机译:在本文中,我们确定了四元数样本协方差矩阵的经验光谱分布极限。由Bai和Silverstein(对大尺寸随机矩阵进行频谱分析,Springer,纽约,2010年)和Marenko和Pastur(Matematicheskii Sb,114:507-536,1967)推动,我们可以扩展实数或复数样本协方差的结果四元数情况的矩阵。假设是一个四元数随机矩阵。对于每个条目,它们是具有共同均值和方差的独立随机四元数变量。结果表明,四元数样本协方差矩阵的经验光谱分布收敛于Marenko-Pastur定律,分别为和(0 +无穷大)。

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