The method of upper and lower solutions and monotone technique for impulsive differential equations with variable moments

In this paper, we initiate the study of the method of upper and lower solutions and monotone iterative technique for impulsive differential equations with variable moments. Because of the difficult nature of the problem, we shall restrict ourselves to a simple situation which, as we shall see, presents enough complications.     

一阶线性微分方程组的一种解法

利用矩阵知识给出了一阶线性微分方程组的一种用公式表达的解法,其优点在于一方面可以避免繁琐的复矩阵运算以及求复特征向量的运算,另一方面可以简化求解过程.     

Factor models in high-dimensional time series—A time-domain approach

High-dimensional time series may well be the most common type of dataset in the so-called “big data” revolution, and have entered current practice in many areas, including meteorology, genomics, chemometrics, connectomics, complex physics simulations, biological and environmental research, finance and econometrics. The analysis of such datasets poses significant challenges, both from a statistical as well as from a numerical point of view. The most successful procedures so far have been based on dimension reduction techniques and, more particularly, on high-dimensional factor models. Those models have been developed, essentially, within time series econometrics, and deserve being better known in other areas. In this paper, we provide an original time-domain presentation of the methodological foundations of those models (dynamic factor models usually are described via a spectral approach), contrasting such concepts as commonality and idiosyncrasy, factors and common shocks, dynamic and static principal components. That time-domain approach emphasizes the fact that, contrary to the static factor models favored by practitioners, the so-called general dynamic factor model essentially does not impose any constraints on the data-generating process, but follows from a general representation result.     

Sparse random graphs: Eigenvalues and eigenvectors

In this paper, we prove the semi‐circular law for the eigenvalues of regular random graph G_n,d in the case d →∞, complementing a previous result of McKay for fixed d. We also obtain a upper bound on the infinity norm of eigenvectors of Erd?s–Rényi random graph G(n,p), answering a question raised by Dekel–Lee–Linial. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2012     

亏损振系广义状态向量灵敏度的移频算法

由于亏损系统的状态向量系线性相关,故无法实现与非亏损系统类似的解耦及控制,这为亏损系统灵敏度分析带来很大困难。针对这个问题本文摒弃一般状态向量系,首先引入广义状态向量及其伴随向量理论,利用它们具有的良好规范正交关系,实现了灵敏度控制方程解耦,其次使用移频技术,实现了亏损系统状态矩阵的广义状态向量的灵敏度分析。该方法可用于求解亏损系统各频段广义特征向量的灵敏度,算法结构紧凑,易于理解和实施。数值算例结果表明,该算法是可行和有效的。     

Eigenvector sensitivity under general and structured perturbations of tridiagonal Toeplitz‐type matrices

The sensitivity of eigenvalues of structured matrices under general or structured perturbations of the matrix entries has been thoroughly studied in the literature. Error bounds are available, and the pseudospectrum can be computed to gain insight. Few investigations have focused on analyzing the sensitivity of eigenvectors under general or structured perturbations. This paper discusses this sensitivity for tridiagonal Toeplitz and Toeplitz‐type matrices.     

关于矩阵对角化的探讨

通过示例探讨了一类可对角化矩阵实施对角化的具体过程.     

Some theoretical comparisons of refined Ritz vectors and Ritz vectors

Refined projection methods proposed by the author have received attention internationally. We are concerned with a conventional projection method and its refined counterpart for computing approximations to a simple eigenpair (A, x) of a large matrix A. Given a subspace ω that contains an approximation to x, these two methods compute approximations (μ,x) and (μ,x) to (λ, x), respectively. We establish three results. First, the refined eigenvector approximation or simply the refined Ritz vector x is unique as the     

对称矩阵的两特征值问题

介绍了对称矩阵的两特征值问题,并给出了计算公式.     

对两道线性代数考研试题的讨论

对一道线性代数考研题在复数域上进行了解答和实现,解释了另一道线性代数考研题中正交向量选取的任意性.