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谱半径

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In this paper,two new methods of estimating are given and proved for the upper and lower bounds on the spectral radius of a nonnegative matrix ,which is based on two special matrices.

借助两个新的矩阵得到非负矩阵谱半径的两个新估计及其证明,并通过实例与以往的结论作比较,验证了这些估计的有效性及精确度。

At the same time, the sufficient and necessary conditions for holding the control system robust stability are analyzed, and the stability criterion in terms of the spectral radius is presented.

分析了控制系统保证鲁棒稳定性的充要条件,给出基于谱半径的稳定判据。

Firstly, we present some sharp upper bounds on the adjacency spectral radius of graphs, and show that these bounds are somewhat better than the known ones.

首先,我们给出一些图的邻接谱半径的一些新的可达上界,并说明这些新结果在一定情形下比已有的结果要好。

In chapter 2, for the iterative matrix M~(-1)N in solving linear system, upper bounds of the spectral radius of some iterative matrix are discussed.

第二章针对迭代求解线性方程组中的迭代矩阵M~(-1)N,讨论了其谱半径的上界估计。

Among all the eigenvalues of Laplacian matrix, the most important is thelargest Laplace eigenvalue, which is called the Laplacian spectral radius of a graph.

在图的拉普拉斯特征值中,最重要的一个即是图的最大拉普拉斯特征值,称为图的Laplace谱半径

By the means of combinatorial matrix, the relation between minimum degree of connected graph and upper bound of spectral radius was carefully depicted.

利用组合矩阵方法,精细地刻画出连通图的最小度与谱半径的上界之间的关系,在一定条件下改进了以前的一个结果。

The results not only is that problem of estimates of upper bounds of the spectral radius for some iteration matrices is solved but also convenient for apply.

解决了以往讨论迭代矩阵谱半径的估值问题,且使用方便。

In chapter 3, based on the relationship between the minimal eigenvalue and the spectral radius of non-negative matrices, we derive some others upper and lower bounds on irreducible M-matrices.

第三章利用M矩阵的最小特征值与非负矩阵谱半径之间的关系,给出了不可约M矩阵最小特征值上下界的几个估计式。

The Laplacian matrix of G is the difference of degree matrix of G and the adjacent matrix of G, And the Laplacian spectral radius of a graph is the maximum eigenvalue of the Laplacian matrix of G.

图G的拉普拉斯矩阵为图G的度矩阵和它的邻接矩阵之差,而图G的拉普拉斯谱半径为图G的拉普拉斯矩阵绝对值最大的特征值。

For example,,,where .2.Convergence of the iterative method: firstly I give a new upper bound for the spectral radius of iterative matrix , where is a double strictly diagonal dominant matrix.

迭代法的收敛性分析:首先给出了一般迭代阵谱半径新的上界估计,其中矩阵为双严格对角占优矩阵,是一种比严格对角占优更广泛的矩阵类。

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