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Lower bounds for the largest eigenvalue of a symmetric matrix under perturbations of rank one

机译:一阶扰动下对称矩阵最大特征值的下界

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摘要

Let A=(a_(ij)) denote a real symmetric matrix of order n and define u as the vector of all ones in Rn. A classical lower bound for the largest eigenvalue of A is given by ytAy=yTy with y=u. Some new developments were recently suggested by Walker and Van Mieghem [S.G. Walker and P. Van Mieghem, On lower bounds for the largest eigenvalue of a symmetric matrix, Linear Algebra Appl. 429 (2008), pp. 519-526] by applying this classical bound to suitable transforms of A. In this short note, it is shown that the approach of Walker and Van Mieghem can be used with choices other than y = u in order to improve classical inequalities when considering matrix perturbations of rank one.
机译:令A =(a_(ij))表示n阶的实对称矩阵,并将u定义为Rn中所有1的向量。 A的最大特征值的经典下界由ytAy = yTy和y = u给出。 Walker和Van Mieghem [S.G. Walker和P. Van Mieghem,关于对称矩阵的最大特征值的下界,线性代数应用。 429(2008),pp。519-526]通过将这种经典约束应用于A的适当变换。在此简短说明中,表明Walker和Van Mieghem的方法可以用于除y = u之外的其他选择在考虑一阶矩阵扰动时改善经典不等式。

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