Convergence of the empirical spectral distribution of Gaussian matrix-valued processes
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DOI: 10.1214/18-ejp203
Abstract: For a given normalized Gaussian symmetric matrix-valued process $Y^{(n)}$, we consider the process of its eigenvalues $\{(\lambda_{1}^{(n)}(t),\dots, \lambda_{n}^{(n)}(t)); t\ge 0\}$ as well as its corresponding process of empirical spectral measures $\mu^{(n)}=(\mu_{t}^{(n)}; t\geq0)$. Under some mild… read more here.
Keywords: convergence; matrix valued; empirical spectral; process ... See more keywords