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arXiv 1612.06552math-phcond-mat.dis-nncond-mat.stat-mechmath.MP
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基于随机矩阵理论的大时滞相关矩阵谱

Spectra of large time-lagged correlation matrices from Random Matrix Theory

Maciej A. Nowak, Wojciech Tarnowski

摘要:

我们使用随机矩阵理论的工具,分析了大的,时滞相关矩阵的频谱特性。我们比较预测的一维光谱,根据文献中已经提出的方法。利用自由随机变量方法和图解技巧,解决了一般随机矩阵问题,即矩阵$\frac{1}{T}XAX^{\dagger}$的谱,其中$X$是$N\times T$高斯随机矩阵,$A$是\textit{any} $T\times T$,不一定是对称(Hermitian)矩阵.作为一个特殊的应用,我们提出了大滞后相关矩阵的谱特征作为一个功能的时间滞后的深度。我们还分析了时滞矩阵的左右特征向量相关的性质。我们积极验证我们的结果通过数值模拟。

英文摘要:

We analyze the spectral properties of large, time-lagged correlation matrices using the tools of random matrix theory. We compare predictions of the one-dimensional spectra, based on approaches already proposed in the literature. Employing the methods of free random variables and diagrammatic techniques, we solve a general random matrix problem, namely the spectrum of a matrix $\frac{1}{T}XAX^{\dagger}$, where $X$ is an $N\times T$ Gaussian random matrix and $A$ is \textit{any} $T\times T$, not necessarily symmetric (Hermitian) matrix. As a particular application, we present the spectral features of the large lagged correlation matrices as a function of the depth of the time-lag. We also analyze the properties of left and right eigenvector correlations for the time-lagged matrices. We positively verify our results by the numerical simulations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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