广义循环矩阵的特征值、逆、行列式值及在结构计算中的应用

给出求解广义循环矩阵的特征值、逆、行列式值及方程组的一种新的分解算法。它将原问题分解为一系列相互独立的子问题。和原问题相比，子问题具有较小的维数，因此它具有更好的特性和更小的舍入误差。特别是，能够带来较高的计算效率。数值算例和在结构计算中的应用表明算法是适用的。

Eigenvalue, Inverse Matrix, Determinant of Generalized Cycle Matrix and Its Application in Computation Structures

A kind of new partitioning algorithm is presented. The algorithm solves the eigenvalue, inverse matrix and determinant of the generalized cycle matrixes and a system of linear equations with the generalized cycle coefficient matrix. The original problem is partitioned into a series of independent subproblems. Compared with the original problem, the dimensions of all these subproblems are very small. This point ensures that it has a better conditioning and gives smaller round off errors. More importantly, the technique leads to a higher efficiency of computation. Some numerical examples and application in the computation structures show that the methods are practical.