On the bounds of maximal entries in the principal eigenvector of symmetric nonnegative matrix

The upper bound of maximal entries in the principal eigenvector of a simple undirected connected graph is investigated in [Linear Algebra Appl. 310 (2000) 129]. We further investigate the maximal entry y^max_p in the principle eigenvector of symmetric nonnegative matrix with zero trace and obtain both sharp upper and lower bounds on the y^max_p. Particularly, this result answers the open question given in the above-mentioned reference     

Some New Results on the Eigenvector Centrality

In this article we establish new results on the components of the principal eigenvector in an undirected graph. Those results are particularly significant in relation to the concept of centrality in social networks. In particular degree centrality and eigenvector centrality are compared. We find further conditions, based on the spectral radius, on which nodes with highest degree centrality are also the most eigencentral.     

Jacobi矩阵逆特征问题解存在的条件

1 引言 对如下形状的n阶实对称三对角矩阵     

On the jackknife statistics for eigenvalues and eigenvectors of a correlation matrix

This paper deals with some problems of eigenvalues and eigenvectors of a sample correlation matrix and derives the limiting distributions of their jackknife statistics with some numerical examples.     

一类矩阵特征值的不等式及其在Fischer不等式证明中的应用

Hadamard和Fischer不等式在矩阵研究中起重要作用.已有大量文献研究此两不等式的新证明、推广、细化及应用.本文研究了和实对称正定矩阵相关的一类矩阵的特征值,并建立了关于这类矩阵特征值乘积范围的一个不等式,利用此不等式证明了行列式的Fischer和Hadamard不等式.     

The state space reconstruction technology of different kinds of chaotic data obtained from dynamical system

Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a theorem of Takens draws on the ideas from the generalized theory of information known as singular system analysis. We illustrate this technique by numerical data from the chaotic region of the chaotic experimental data. The method of the singular-value decomposition is used to calculate the eigenvalues of embedding space matrix. The corresponding concrete algorithm to calculate eigenvectors and to obtain the basis of embedding vector space is proposed in this paper. The projection on the orthogonal basis generated by eigenvectors of timeseries data and concrete paradigm are also provided here. Meanwhile the state space reconstruction technology of different kinds of chaotic data obtained from dynamical system has also been discussed in detail. The project supported by the National Natural Science Foundation of China (19672043)     

利用慢度曲面研究立方晶系晶体的铁弹相变

讨论了慢度曲面与声学模软化之间的关系.立方晶系晶体声学模的软化即对应其在某一方向上的最大慢度,软模的本征矢的方向即为与最大慢度相对应的声学模的偏振化方向.通过求解Christoffel方程可找到某些方向上的最大慢度和与它们对应的声学模的偏振化方向.从而晶体在本征铁弹相变前后结构对称性的变化可以通过分析Christoffel方程的解及利用居里原理来确定.