@Article{AAM-35-2,
author = {Liang, Juan and Lai, Jiangzhou and Qiang, Niu},
title = {Asymptotic Eigenvalue Estimation for a Class of Structured Matrices},
journal = {Annals of Applied Mathematics},
year = {2019},
volume = {35},
number = {2},
pages = {152--158},
abstract = {<p style="text-align: justify;">In this paper we consider eigenvalue asymptotic estimations for a class of
structured matrices arising from statistical applications. The asymptotic upper
bounds of the largest eigenvalue ($λ$<sub>max</sub>) and the sum of squares of eigenvalues $(\sum\limits_{i=1}^nλ_i^2)$ are derived. Both these bounds are useful in examining the stability of certain Markov process. Numerical examples are provided to illustrate
tightness of the bounds.</p>},
issn = {},
doi = {https://doi.org/2019-AAM-18074},
url = {https://global-sci.com/article/72692/asymptotic-eigenvalue-estimation-for-a-class-of-structured-matrices}
}