首页> 外文期刊>Journal of Multivariate Analysis: An International Journal >Extreme eigenvalue distributions of some complex correlated non-central Wishart and gamma-Wishart random matrices
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Extreme eigenvalue distributions of some complex correlated non-central Wishart and gamma-Wishart random matrices

机译:一些复杂的相关非中心Wishart和gamma-Wishart随机矩阵的极值特征值分布

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摘要

Let W be a correlated complex non-central Wishart matrix defined through W=XHX, where X is an n×m(n≥m) complex Gaussian with non-zero mean Υ and non-trivial covariance σ. We derive exact expressions for the cumulative distribution functions (c.d.f.s) of the extreme eigenvalues (i.e., maximum and minimum) of W for some particular cases. These results are quite simple, involving rapidly converging infinite series, and apply for the practically important case where Υ has rank one. We also derive analogous results for a certain class of gamma-Wishart random matrices, for which ΥHΥ follows a matrix-variate gamma distribution. The eigenvalue distributions in this paper have various applications to wireless communication systems, and arise in other fields such as econometrics, statistical physics, and multivariate statistics.
机译:令W为通过W = XHX定义的相关复非中心Wishart矩阵,其中X为n×m(n≥m)复高斯,均值Υ非零且协方差σ为零。对于某些特定情况,我们得出W的极端特征值(即最大和最小值)的累积分布函数(c.d.f.s)的精确表达式。这些结果非常简单,涉及快速收敛的无限级数,并且适用于Υ排名第一的实际情况。我们还针对某类γ-Wishart随机矩阵推导相似的结果,其中ΥHΥ遵循矩阵变量γ分布。本文的特征值分布在无线通信系统中有各种应用,并且出现在其他领域,例如计量经济学,统计物理学和多元统计。

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