On singular value distribution of large dimensional data matrices whose columns have different correlations

preprint2020arXivOpen access

Abstract

Suppose Yn=(y1,⋯ ,yn)\mathbf Y_n=(\mathbf y_1,\cdots,\mathbf y_n) is a p×np\times n data matrix whose columns yj,1≤j≤n\mathbf y_j, 1\leq j\leq n have different correlations. The asymptotic spectral property of Sn=1nYnYn∗\mathbf S_n=\frac1n\mathbf Y_n\mathbf Y^*_n when pp increase with nn has been considered by some authors recently. This model has known an increasing popularity due to its widely applications in multi-user multiple-input single-output (MISO) systems and robust signal processing. In this paper, for more convenient applications in practice, we will investigate the spectral distribution of Sn\mathbf S_n under milder moment conditions than existing work. We also discuss a potential application in sample classification.

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