Computing of Extremal Characteristic Values of Symmetric Matrices by Individual Homotopy Algorithm

R. Baik
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Abstract

In this pape, we develop a new Homotopy method called the individual Homotopy method to solve the symmetric eigenproblem. The individual Homotopy method overcomes notable drawbacks of the existing Homotopy method, namely, (i) the possibility of breakdown or having a slow rate of convergence in the presence of clustering of the eigenvalues and (ii) the absence of a definite criterion to choose a step size that guarantees the convergence of the method. On the other hand, we also have a good approximations of the largest eigenvalue of a symmetric matrix from Lanczos algorithm. We apply it for the extremal eigenproblem of a very large symmetric matrix with good initial points.
用个体同伦算法计算对称矩阵的极值特征值
本文提出了一种新的求解对称本征问题的同伦方法——个体同伦方法。个体同伦方法克服了现有同伦方法的明显缺点,即(i)存在特征值聚类时可能崩溃或收敛速度慢,(ii)缺乏确定的准则来选择保证方法收敛的步长。另一方面,我们也从Lanczos算法中得到了对称矩阵最大特征值的一个很好的近似。我们将其应用于具有良好初始点的超大对称矩阵的极值特征问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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